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AI/ML Engineer, Internal Platforms

micro1

Location: Remote — Worldwide Advertised pay: USD 220,000–300,000 / yearly Work arrangement: Worldwide remote Employment: Full Time Posted: October 6, 2026 Freshness: Aging listing
Disclosure5 of 5 core facts statedReview uncertainties
Last source observationSource check unavailableObservation is not employer confirmation.
Application destinationNot providedReview the application route and source evidence in the full report below.

Executive opportunity brief

The decision in one screen

A compact evidence-first read of compensation, flexibility, mobility and what still needs verification. No universal quality score is used.

Compensation positionUSD 220,000–300,000 / year5 current same-currency observations
Work flexibilityWorldwide remoteBased only on stated location/work-arrangement evidence.
Decision evidence5 of 5 core facts knownThis listing states more core decision facts than the median role in the current sample.
Mobility evidenceSponsorship not establishedUnknown evidence is not treated as unavailable.
Current alternatives1237 current same-family rolesCurrent HPJ inventory, not the whole labor market.
Negotiation readinessNegotiation evidence available: advertised pay range, current same-currency market context, strong decision evidence.Use the private Offer & Negotiation Lab below if an offer arrives.
Watch closely: Recent source observation is not established · Direct application destination is not provided

Fast read

Opportunity DNA

There is a useful advantage here: location flexibility looks unusually broad. Still, the salary benchmark is still shallow could change the fit.

May appeal in aRemote-first search
PayRange available

The range is usable, but the comparable sample is still too shallow for a strong relative-pay call.

FlexibilityBroad location freedom

No material geography, office-attendance or timezone restriction is visible in the available wording.

Entry pathRequirements unclear

The listing does not make the minimum education or experience threshold clear enough yet.

MobilityNot established

Sponsorship and relocation support are not clear from the current listing.

ApplicationSome process detail

Part of the application route can be assessed, but the full external process may contain additional steps.

TraceabilityRecheck availability

Current renewable source evidence is limited, so confirm the vacancy is still open before sharing sensitive information.

This fingerprint summarizes what is clear, constrained or still unanswered in the current listing. It is a reading aid, not an overall job score.

Decision evidence check

5 of 5 core facts stated

This checks whether the listing states the facts that commonly change an employment decision. It measures disclosure completeness, not whether the opportunity is good or bad.

Facts already stated

  • Compensation
  • Work arrangement
  • Advertised location
  • Application closing time
  • Employment type

Core evidence complete

All five core facts are stated. Other details can still matter, so continue with the qualification, mobility, employer and application checks below.

Advertised location is not proof of work authorization, sponsorship, or legal eligibility. Unknown information is not a negative score; verify those questions separately.

Decision levers

What could make or break the fit?

Reasons to look closer

  • Location flexibility looks unusually broad: The available wording supports high Remote Freedom without a material geography, office-attendance or timezone restriction showing up.

Trade-offs to weigh

  • The salary benchmark is still shallow: Pay is disclosed, but the current comparison pool is too small for a strong relative-pay conclusion.

Questions worth asking before you invest more time

  • Confirm whether a degree is actually required, preferred, or replaceable with equivalent experience.
  • Confirm the actual minimum experience requirement rather than assuming preferred background is mandatory.
  • Ask whether visa sponsorship is available before investing significant time in the application.
  • Verify that the vacancy is still active on the authoritative employer or application destination before sharing sensitive information.

These questions come from details the listing leaves open. An unanswered point is not treated as a disadvantage.

Opportunity neighborhood

Keep your options open

These live roles sit close enough to this opportunity to make useful comparison points. Look across several employers before deciding what pay, flexibility or access trade-offs you are willing to accept.

FBS Associate Data Engineer

Capgemini Technology Services · Remote — Worldwide

Salary not disclosed Worldwide remote 4/5 core facts

Why it is nearby: Same seniority band · Similar work arrangement · Same employment type

AI Engineer, GTM

Cresta · USA

USD 150,000–230,000 / year Region-restricted remote 4/5 core facts

Why it is nearby: Similar work arrangement · Same employment type · Recently posted

About 27% lower advertised midpoint

Different angle: Seniority is not explicit

This neighborhood is drawn from current inventory in the same broad occupation. Similarity is based on explicit listing facts; missing details do not count against a job.

Role market context

How much current choice is visible around this kind of work?

This compares the vacancy with current High Paid Job inventory in the broad Data & AI roles family. It describes visible choice and disclosure, not future demand or career quality.

Current visible roles1,237

200 most recent current roles sampled for the disclosure measures below.

Employers represented141

Distinct employers in the bounded current sample, not an estimate of all employers hiring in the market.

Decision-ready disclosure36%

Current sampled roles stating at least four of the five Core Decision Facts.

Compensation stated37%

Requires a numeric amount, explicit ISO currency and supported pay period.

Work arrangement stated91%

Listings with explicit enough remote, hybrid or on-site evidence to classify.

Stated closing time24%

Missing deadline evidence remains unknown and is not interpreted as an open-ended application window.

Disclosure comparison: This listing states more core decision facts than the median role in the current sample. This listing: 5/5 · sample median: 3.0/5.

Currencies with explicit pay evidence in the sample: USD (60) · EUR (8) · GBP (4) · CAD (1). Raw amounts across different currencies are not compared.

This describes current visible High Paid Job inventory in the same broad occupation family. Percentages use a bounded recent sample and are not a forecast, a complete labor-market census or an employer-quality measure.

Constraint opportunity lab

What changes the size of the current opportunity pool?

Each line applies one stricter evidence-based constraint to the same bounded current role-family sample. It helps you see the trade-off in visible choice without deciding which trade-off is right for you.

Require explicit sponsorship or relocation support 0 / 200 0%

Counts only affirmative or possible sponsorship evidence, or relocation explicitly offered. Unknown is not treated as no.

Require worldwide remote evidence 17 / 200 9%

A much stricter subset: only listings with explicit worldwide-remote evidence remain.

Keep this advertised salary floor in the same currency 17 / 59 29%

Only same-currency opportunities with usable annualized pay enter this comparison. Other currencies are not converted or treated as lower.

Require a remote-listed arrangement 63 / 200 32%

Counts roles explicitly classified as worldwide remote, region-restricted remote or remote with restrictions still unclear.

Require at least four Core Decision Facts 72 / 200 36%

Shows the subset with enough stated evidence for a more informed first comparison.

Require usable compensation disclosure 73 / 200 37%

Requires amount, explicit ISO currency and a supported pay period. Missing pay evidence remains unknown.

Stay around the same seniority band 95 / 200 48%

Includes roles whose seniority is genuinely unspecified rather than assuming they belong to another level.

Keep the same employment type 127 / 136 93%

Uses only roles with a stated employment type.

These are counterfactual filters over a bounded sample of current HPJ inventory in the same broad occupation family. They show how visible choice changes when one evidence-based constraint is applied; they do not tell you which constraint you should choose or predict hiring outcomes. The calculation uses the 200 most recent current roles from 1237 visible roles in this broad family.

Salary transparency context

Is pay disclosure typical for this kind of role?

This listing states usable structured compensation. About 37% of the bounded current role sample does the same.

This listingUsable pay stated

Compensation counts only when amount, ISO currency and supported pay period are all known.

Current same-role sample37%

Pay disclosure is limited in the current role sample.

Current employer pattern51%

This employer’s current pay-disclosure rate is broadly similar to the current same-role sample.

This compares salary-disclosure behavior in current visible listings. It does not compare raw salary amounts across currencies, infer undisclosed pay as zero, or rate employer quality.

Private offer & negotiation lab

Turn an offer into evidence, not guesswork

Enter an annual base offer and, if you want, your own target. HPJ compares only within one explicit currency and never chooses a target for you.

Advertised annualized payUSD 220,000–300,000 / yearListing evidence only.
Current comparable medianUSD 170,00055 current sampled roles
Current upper quartileUSD 239,378Current HPJ inventory context, not a salary recommendation.

Negotiation evidence available: advertised pay range, current same-currency market context, strong decision evidence.

Enter an annual base offer to compare it with explicit same-currency evidence. HPJ will not suggest a target for you.

Review the full package · 10 terms

Mark what is confirmed, what needs clarification and what you want to prioritize. These choices and notes stay in this browser.

Base payKnown

Usable advertised compensation is available.

Bonus / commissionVerify

Variable compensation is mentioned; verify amount, formula, target and eligibility.

Equity / long-term incentivesMentioned

Equity or long-term incentive language is mentioned; verify grant type, vesting and valuation basis.

Retirement / pensionMentioned

Retirement or pension benefits are mentioned; verify employer contribution and vesting.

Health benefitsVerify

Health-benefit language is mentioned; verify coverage, dependants and employee cost.

Paid leaveMentioned

Paid-leave language is mentioned; verify the exact entitlement and carry-over rules.

Work arrangementKnown

A work-arrangement signal is available; verify schedule details before relying on it.

RelocationVerify

Relocation support not established

Visa / work authorizationVerify

Sponsorship not established

Review timingVerify

A review cycle is mentioned; verify timing and whether compensation can change at that review.

Questions worth taking into the offer conversation

  • Is there a bonus, commission or other variable-pay component, and how is it calculated?
  • What health coverage is included and what costs remain with the employee?
  • If relocation is relevant, what expenses, timing and repayment conditions are covered?
  • What exact sponsorship or work-authorization conditions apply to this role?
  • When is the first performance and compensation review after joining?

Occupation intelligence

What broader career references connect to this role?

HPJ uses broad comparison families for current-market analysis. External taxonomy results are reference candidates for that broad family, not a declaration that this vacancy has been authoritatively classified into a specific occupation.

HPJ comparison familyData & AI roles
Adjacent families worth exploringSoftware engineering roles · Product roles

European occupation references

This service uses the ESCO classification of the European Commission.

U.S. occupation references

This site incorporates information from O*NET Web Services by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). O*NET® is a trademark of USDOL/ETA.

Career reference research

Skills worth investigating

Official occupational context, paired with exact phrases visible in this vacancy. It is not a skills test or an applicant-fit score.

ESCO · European occupation

data scientist

Usually essential in this ESCO occupation
  • handle data samples
  • integrate gender dimension in research
  • deliver visual presentation of data
  • scientific literature
  • promote the participation of citizens in scientific and research activities
  • perform data cleansing
  • manage intellectual property rights
Context-dependent ESCO skills
  • MDX
  • scientific computing
  • digital curation
  • integrate ICT data
  • state estimation

O*NET · U.S. occupation

Data Scientists

O*NET occupation skills
  • Mathematics
  • Critical Thinking
  • Reading Comprehension
  • Complex Problem Solving
  • Programming
  • Active Learning
  • Speaking
  • Active Listening
Build my private skill preparation brief Your evidence · Practice · Interview questions

Plan how you might demonstrate or investigate occupational skills. These are broad-family reference examples, not confirmed vacancy requirements. Nothing you enter is sent to High Paid Job.

handle data samplesESCO · Essential · Listing mention unknown
integrate gender dimension in researchESCO · Essential · Listing mention unknown
deliver visual presentation of dataESCO · Essential · Listing mention unknown
scientific literatureESCO · Essential · Listing mention unknown
promote the participation of citizens in scientific and research activitiesESCO · Essential · Listing mention unknown
perform data cleansingESCO · Essential · Listing mention unknown
manage intellectual property rightsESCO · Essential · Listing mention unknown
MDXESCO · Optional · Listing mention unknown
scientific computingESCO · Optional · Listing mention unknown
digital curationESCO · Optional · Listing mention unknown
integrate ICT dataESCO · Optional · Listing mention unknown
state estimationESCO · Optional · Listing mention unknown
MathematicsO*NET · Skills · Listing mention unknown
Critical ThinkingO*NET · Skills · Listing mention unknown
Reading ComprehensionO*NET · Skills · Listing mention unknown
Complex Problem SolvingO*NET · Skills · Listing mention unknown
ProgrammingO*NET · Skills · Listing mention unknown
Active LearningO*NET · Skills · Listing mention unknown
SpeakingO*NET · Skills · Listing mention unknown
Active ListeningO*NET · Skills · Listing mention unknown

Private to this browser. Up to 20 reference skills; not a qualification assessment or hiring prediction.

Useful next question: Which of these occupational reference skills does the hiring manager actually expect for this specific role, and what evidence would demonstrate them?

These skills belong to one reference occupation selected for HPJ’s broad career family, not a verified classification of this vacancy. Text overlap only means a phrase appears in the available listing text; it does not establish an employer requirement, your proficiency, or a qualification gap. A missing mention is unknown, not a deficit.

Adjacent current roles to investigate

Adjacent-family roles are exploration prompts from current HPJ inventory. They are not inferred qualification matches and they do not imply a promotion path.

Career move map

What sits one step away?

This listing is currently read as Mid-career. Nearby roles one visible seniority step away can help you judge whether to widen the search, stretch upward or compare the responsibilities more carefully.

Stretch direction

Senior / lead

Senior Data Engineer

Leidos · Remote — Worldwide

Similar work arrangement · Same employment type · Recently posted Advertised midpoint is about 42% lower

These are live roles one visible seniority step away in the same broad occupation family. They can reveal nearby options, but they are not a guaranteed promotion path and do not account for your personal experience.

Skill bridge

What does this role connect to?

AWS is one of the signals this listing shares with skills appearing often across current Data & AI roles opportunities.

Skills named in this listing

AWSAzureGoogle CloudLarge Language ModelsPython

Shared with the current career sample

  • AWS Seen in 35 sampled listings
  • Azure Seen in 20 sampled listings
  • Google Cloud Seen in 17 sampled listings
  • Large Language Models Seen in 38 sampled listings

Combinations also appearing together

  • AWS + Python appeared together in 29 sampled listings
  • Large Language Models + Python appeared together in 25 sampled listings

Application edge

  • If these skills match your background, prepare one concrete example that shows how you used AWS, Azure, and Google Cloud rather than relying on a keyword-only claim.
  • The listing mentions extra application steps. Review those requirements before starting so you can prepare the requested material in one pass.

If the named skills are genuinely transferable in your own experience, the occupation map also points to adjacent current families worth researching: Software engineering roles and Product roles. This is exploration context, not a qualification match.

Skill signals come from explicit text mentions. A mention is not automatically a requirement, and absence from the current top-skill list does not make a skill rare or unimportant. The current career comparison draws on 120 sampled listings; 119 contain a recognized skill signal.

Application Decision Lab

Turn the listing into a preparation plan

Separate what the listing actually states from what you still need to prepare or verify. Your selections and short notes stay in this browser and are never submitted to High Paid Job.

Listing mention

AWS

This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.

Listing mention

Azure

This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.

Listing mention

Google Cloud

This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.

Listing mention

Large Language Models

This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.

Listing mention

Python

This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.

Application step

Prepare for a stated application step

An assessment, test or work-sample step is explicitly mentioned.

Questions worth resolving before you rely on the opportunity

  • Work authorization / sponsorship: If sponsorship or work authorization matters to you, what exact immigration or employer-sponsorship conditions apply to this role?

Decision analysis

What the listing really tells you

Useful decision context

For AI/ML Engineer, Internal Platforms at micro1, the most useful clues right now are pay is visible, but the benchmark is still thin, remote flexibility can be weighed properly, and the visible application effort can be estimated. Looking at them together makes the trade-offs easier to see.

Pay is visible, but the benchmark is still thin

A usable USD salary is available, but there are not enough comparable current observations for a strong percentile statement yet.

Remote flexibility can be weighed properly

The work-location pattern is “Highly location-flexible”, with Remote Freedom at 96/100.

The visible application effort can be estimated

Application path not classified · 1 visible process step. The external application may contain additional steps that are not visible from the listing itself.

How this analysis is assembled

This read combines the structured details currently available for pay, flexibility, qualifications, mobility, application effort and source continuity. Missing facts are left open for you to verify.

Analysis evidence coverage

How much analysis can the current evidence support?

55%Partial analysis evidence coverage
55%
Current-sample pay positionInsufficient comparable salary sample

Only 5 comparable salary observations are available. At least 10 are needed before showing a High Pay Score.

Remote Freedom evidence96 / 100

Measures observable location flexibility and explicit restrictions; it does not determine whether remote work is personally desirable.

Salary evidence qualityHigh confidence · Focused salary range

The configured source supplied structured salary fields, a usable currency and a focused comparison value.

Listing freshnessAging listing

The listing was posted about 34 days ago. Verify that it is still accepting applications.

Source provenance evidenceSource evidence unavailable

There is not enough source history yet to describe how well this listing can be traced across current feeds.

There is no universal opportunity score because pay, flexibility and access matter differently to different people. Compare Jobs lets you weight the evidence around your own priorities.

Decision checklist

What is supported, uncertain or worth checking?

This checklist separates supported strengths, visible cautions and missing evidence. It is not an overall recommendation or guarantee that the job is suitable for you.

Supported strengths

  • The available work-location evidence indicates strong location flexibility.

Visible cautions

  • The listing was posted about 34 days ago. Verify that it is still accepting applications.
  • Some compensation may be variable or performance-based. Confirm the guaranteed base amount before comparing headline pay.

Still unknown

  • There is not enough comparable salary evidence to establish this job’s current pay position.
  • Visa sponsorship is not established by the available listing data.
  • Current source provenance is insufficient for a stronger traceability assessment.
  • The directness of the application route is not established.

Qualifications & access

What qualifications are explicitly stated?

Entry-barrier evidence limited

EducationEducation requirement not established
Required experience evidenceExperience requirement not established
Explicit required barriers0
Explicit access signals0

Qualification signals come from explicit listing wording. Anything not mentioned remains unknown, so silence is never treated as proof that a degree, experience, licence or other requirement is unnecessary.

Pay vs. barriers

Opportunity Efficiency not assessed

The current pay position is not reliable enough to weigh compensation against the stated barriers.

Evidence gaps that could change this interpretation
  • Current comparable pay position is unavailable.
  • Education requirement is not established.
  • Required prior-experience level is not established.

This section weighs pay context against clearly stated barriers without collapsing unlike requirements into one universal score. Degree, experience, licensing, clearance and location limits remain separate, and missing qualification details stay unknown.

Beyond the headline

Not enough evidence for a hidden-value finding

Potential hidden value appears only when several distinct non-pay advantages are actually supported. Missing requirements or benefits are never counted as positives.

Strong location flexibility

The observable Remote Freedom evidence is strong and contains few explicit restriction signals.

Hidden Value is an experimental evidence summary, not an investment-style score or guarantee of employability. It only uses explicit current listing evidence and does not infer that an unmentioned qualification is unnecessary.

Explainable opportunity highlight

Why this opportunity stands out

These are supported signals from the current listing and comparison sample—not a guarantee that this is the best job for you.

Clear compensation evidence

The source provides structured salary information with a comparatively focused range, improving the usefulness of pay comparisons.

Strong remote flexibility

The observable work-location signals indicate unusually strong location flexibility.

Compensation intelligence

How competitive is this pay?

No High Pay Score yet

Only 5 comparable salary observations are available. At least 10 are needed before showing a High Pay Score.

Why this analysis?

  • Only 5 comparable salary observations are available. At least 10 are needed before showing a High Pay Score.
  • Salary confidence: High. The configured source supplied structured salary fields, a usable currency and a focused comparison value.
  • Range quality: Focused salary range.

Employer compensation communication

Pay transparency at micro1

Mixed current pay transparency

This score uses the employer’s current visible listings and combines how often pay is disclosed with how useful those ranges are. Bonus, equity and benefit mentions are shown separately and do not raise the score.

56/100
56%
Salary disclosure51% · 26 of 51 sampled listings
Range qualityMixed range quality
Bonus wording0 current listings
Equity wording5 current listings
Benefits wording7 current listings
Evidence strengthStronger

This pattern comes from the employer’s current visible vacancies. It describes hiring and pay transparency in those listings, not employee satisfaction or a permanent judgement of the employer.

Current employer intelligence

micro1 — current opportunity snapshot

Current opportunities visible51
Salary disclosure51%
Remote-policy evidence coverage100% · 51 of 51 sampled listings
Remote share of known arrangements100%
Worldwide-remote share100%
Known hiring countries0
Sponsorship evidence coverage0% · 0 of 51 sampled listings
Explicit sponsorship outcomes0 confirmed · 0 possible · 0 unavailable
Pattern sample51 of 51 · 100% coverage
Current role-family breadth7
Stated closing-date coverage100%
Relocation evidence coverage0% · 0 explicitly offered
Posted within 7 days20% of listings with a known posting date

Employer Evidence Profile

How often this employer’s current visible sampled vacancies state decision-critical information. These percentages describe evidence coverage, not employer quality.

Compensation51% of sampled current listings

Current sampled listings with advertised compensation evidence.

Work arrangement100% of sampled current listings

Current sampled listings whose work arrangement is clearer than unknown.

Location0% of sampled current listings

Current sampled listings with a supported country signal.

Application timing100% of sampled current listings

Current sampled listings with an explicit closing time.

Posting date100% of sampled current listings

Current sampled listings with a usable posting date.

Sponsorship0% of sampled current listings

Current sampled listings that explicitly indicate confirmed, possible or unavailable sponsorship evidence.

Relocation0% of sampled current listings

Current sampled listings with an explicit relocation signal.

Low coverage means the current visible listings state the information less often. It does not prove that the employer lacks the policy, benefit or support.

Common current occupation families: Legal (6) · Healthcare (3) · Executive (1)

Visible seniority mix: Early-career (7) · Mid-career (23) · Senior / lead (20) · Leadership (1)

Current employment-type mix: Contract (43) · Full time (7) · Part time (1)

Other current roles from this employer

These are other current vacancies visible from the same employer, not endorsements or evidence of future hiring plans.

Current disclosed salary medians by currency

  • USD 169,000 median · 26 disclosed salaries

Questions worth asking this employer

  • What compensation range applies to this role, and which parts of total compensation are fixed versus variable?
  • If work authorization matters to you, what sponsorship policy applies to this specific role and location?
  • If a move is required, is relocation assistance available for this position?

These questions are prompted by missing or thin evidence in the employer’s current visible vacancies. Missing evidence is not treated as a negative judgement.

This employer snapshot uses the employer’s current visible listings. Remote and sponsorship rates use only vacancies with explicit evidence, while missing information stays unknown. Salary medians are shown separately by currency and need at least five disclosed salaries. Zero confirmed sponsorship means none was explicitly found in this sample, not that sponsorship is unavailable.

This snapshot describes the employer’s current visible vacancies—things such as pay disclosure and work arrangement. It is not an employee-satisfaction or hiring-quality rating, and different currencies stay separate.

Work-location intelligence

Remote Freedom

96/100

Highly location-flexible

96%

Why this score?

  • The source describes the role as open worldwide or globally.

Flexibility signals detected

  • Worldwide or global remote eligibility is explicitly indicated.

Remote Freedom measures observable location flexibility only. Unknown work-location information remains unscored. Timezone wording is penalized only when it appears restrictive; general collaboration across time zones is not treated as a restriction. A score does not guarantee legal work eligibility, payroll availability or visa sponsorship.

International applicant intelligence

Visa & relocation signals

Sponsorship status is shown only when the listing provides clear enough wording. Employer history or headquarters location is not used to guess an answer.

Visa sponsorshipSponsorship not established

The available listing details do not contain a clear enough sponsorship statement.

RelocationRelocation support not established

The available listing details do not contain a clear enough relocation statement.

Tradeoff check

What’s the catch?

These are visible conditions worth checking before treating the headline compensation as the whole story:

  • Some compensation may be variable or performance-based. Confirm the guaranteed base amount before comparing headline pay.

Current alternatives

Better-paying alternatives

These current roles show a materially higher annualized salary midpoint in the same broad occupation and currency. Similar seniority, country, work arrangement, employment type and recency are preferred where possible; higher pay alone does not make an alternative a better fit.

About +19900% midpoint

AI Engineer

Jobgether · UK

On-site / hybrid

Why comparable: Same employment type · Recently posted

Check: Seniority is not explicit in the alternative listing.

About +19900% midpoint

AI Engineer

Jobgether · Germany

On-site / hybrid

Why comparable: Same employment type · Recently posted

Check: Seniority is not explicit in the alternative listing.

About +19900% midpoint

AI Engineer

Jobgether · France

On-site / hybrid

Why comparable: Same employment type · Recently posted

Check: Seniority is not explicit in the alternative listing.

Alternatives are drawn from the current inventory rather than presented as application recommendations. A pay difference needs to be meaningful—about 3% or more at the midpoint—and different currencies are not compared.

Application-path intelligence

What can we see about the application process?

Application path not classified

The available provenance is not specific enough to characterize how direct the application route is.

Visible application steps or requirements

  • An assessment, test or work-sample step is explicitly mentioned.

Application effort is estimated from visible listing and source details. Optional steps are kept separate from mandatory ones, and the external form may contain additional requirements that are not visible here.

Application safety context

Application safety check

Limited application-safety evidence

There is not enough observable application-safety evidence to make a stronger statement. Missing evidence is not treated as a negative signal, and source traceability is evaluated separately.

Evidence checked: Listing wording

Before you share money or sensitive information
  • Confirm the vacancy on the employer’s official careers site when practical, especially if a recruiter contacts you outside the listed application path.
  • Check that recruiter email domains and application destinations are consistent with the employer or an identifiable recruiting provider.
  • Do not pay application, processing, training or equipment fees merely to be considered for a job.
  • Do not send cryptocurrency, gift cards, online-banking credentials or PINs as part of an application.
  • Treat unusually fast offers or interviews conducted only through informal messaging channels as reasons to verify the employer independently.

This is a limited safety screen, not employer verification and not a fraud determination. Never send money, cryptocurrency, passwords or sensitive banking credentials merely because a listing appears on a job platform.

Original listing details

The section below comes from the listing source. The decision sections above use the job’s structured pay, location, qualification, mobility and application details to give you additional context.

Job Title: AI/ML Engineer, Internal Platforms

Job Type: Full-time

Location: Remote

The Role

Join our team to build and improve a next-generation AI recruiting agent. You'll develop new capabilities, experiment with the latest LLMs and agent frameworks, and ship production-ready AI features that make the agent smarter, more reliable, and more useful.

What You'll Do

  1. Build and improve AI agent capabilities using modern LLMs.
  2. Develop backend services and APIs in Python.
  3. Design and iterate on prompts, workflows, RAG, and agent orchestration.
  4. Evaluate model performance and continuously improve quality through experimentation.
  5. Collaborate with product and engineering teams to deliver AI-powered features.
  6. Deploy and maintain scalable AI systems in production.
  7. Stay current with the latest AI models, tools, and best practices.

What We're Looking For

  1. Strong Python software engineering skills.
  2. Experience building applications with LLMs and AI APIs.
  3. Familiarity with agent frameworks such as LangChain, LangGraph, or LlamaIndex.
  4. Experience building APIs with FastAPI or similar frameworks.
  5. Experience with cloud platforms (AWS, GCP, or Azure).
  6. Strong problem-solving skills and an experimental mindset.
  7. Excellent communication and collaboration skills.

Preferred Qualifications

  1. Experience shipping AI products or AI agents to production.
  2. Familiarity with RAG, tool calling, model evaluation, or prompt engineering.
  3. Contributions to open-source AI projects or personal AI applications.
  4. Experience working in fast-paced, AI-first environments.

Compensation & Benefits Notice

The national pay range for this full-time position is base salary of $130,000 –$160,000 USD. All employees are eligible for equity compensation, and employees may also receive performance-based bonuses, dependent on role and subject to company policies. micro1 provides a comprehensive benefits package, including up to 100% reimbursement for health-insurance premiums, paid time off, a 401(K) plan with a company match, and additional benefits designed to support a high-performing, remote-first workforce.

micro1 is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation during the application process, reach out to .

Our hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making.

Disclaimer

The information contained in this job posting, including but not limited to role responsibilities, qualifications, compensation, and benefits, is provided for informational purposes only and does not constitute a binding offer of employment. micro1 reserves the right to amend, modify, or withdraw any portion of this posting at its sole discretion and without prior notice. All employment decisions are made in accordance with applicable laws and regulations.

Originally posted on Himalayas