Job intelligence
Sr. AI/ML Engineer (MXC)
AlertMedia
Before relying on the listing: Confirm Compensation and Application closing time with the employer or source. See verification questions
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.
Fast read
Opportunity DNA
This opportunity needs a closer read before drawing a strong conclusion, especially around the pay picture is incomplete.
A financial comparison will need the approved compensation range.
Applicant residence or location appears to be restricted.
Some access and qualification signals are clear, but the overall entry path is neither unusually open nor unusually restrictive.
Sponsorship and relocation support are not clear from the current listing.
Part of the application route can be assessed, but the full external process may contain additional steps.
At least one recent enabled source can still renew this vacancy.
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
3 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
- Work arrangement
- Location eligibility
- Employment type
What to verify next
- Compensation: What is the approved compensation range, and what portion is guaranteed base pay rather than variable compensation?
- Application closing time: Is there a firm application deadline, a rolling review window or no stated closing date?
Unknown information is never converted into a negative score. The questions above exist to prevent missing evidence from being mistaken for a favorable term.
Decision levers
What could make or break the fit?
Reasons to look closer
Nothing stands out strongly enough yet to call a clear advantage. The role may still be attractive for reasons the listing does not spell out.
Trade-offs to weigh
- The pay picture is incomplete: No usable salary range is stated, so a meaningful financial comparison is not possible yet.
- Location rules could change the fit: Applicant residence or location appears to be restricted.
Questions worth asking before you invest more time
- Ask for the approved compensation range before comparing this opportunity financially.
- Confirm whether a degree is actually required, preferred, or replaceable with equivalent experience.
- Ask whether visa sponsorship is available before investing significant time in the application.
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.
Staff Machine Learning Engineer, Retrieval & Targeting
Reddit · Remote — Worldwide
Why it is nearby: Same seniority band · Similar work arrangement · Same employment type
Binance Acceleration Program - Product Data Analyst
Binance · Singapore
Why it is nearby: Same seniority band · Similar work arrangement · Recently posted
Different angle: Different country
Experienced/Senior Machine Learning Engineer - Squad Distribute
Doctrine · Paris
Why it is nearby: Same seniority band · Same employment type · Recently posted
Different angle: Different work arrangement
Senior Analytics Engineer, Finance
Airalo · United Kingdom
Why it is nearby: Same seniority band · Same employment type · Recently posted
Different angle: Different country · Different work arrangement
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.
200 most recent current roles sampled for the disclosure measures below.
Distinct employers in the bounded current sample, not an estimate of all employers hiring in the market.
Current sampled roles stating at least four of the five Core Decision Facts.
Requires a numeric amount, explicit ISO currency and supported pay period.
Listings with explicit enough remote, hybrid or on-site evidence to classify.
Missing deadline evidence remains unknown and is not interpreted as an open-ended application window.
Currencies with explicit pay evidence in the sample: USD (26) · EUR (9) · GBP (4) · CAD (2). 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.
Uses only roles where a country is known. Roles without country evidence are excluded from this denominator.
Counts only affirmative or possible sponsorship evidence, or relocation explicitly offered. Unknown is not treated as no.
A much stricter subset: only listings with explicit worldwide-remote evidence remain.
Requires amount, explicit ISO currency and a supported pay period. Missing pay evidence remains unknown.
Shows the subset with enough stated evidence for a more informed first comparison.
Counts roles explicitly classified as worldwide remote, region-restricted remote or remote with restrictions still unclear.
Uses only roles with a stated employment type.
Includes roles whose seniority is genuinely unspecified rather than assuming they belong to another level.
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 1061 visible roles in this broad family.
Salary transparency context
Is pay disclosure typical for this kind of role?
This listing does not state usable structured compensation. About 21% of the bounded current role sample does.
Compensation counts only when amount, ISO currency and supported pay period are all known.
Pay disclosure is uncommon in the current role sample.
This employer’s current visible listings disclose pay materially less often than 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.
Negotiation evidence available: current same-currency market context.
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.
The approved base-pay range is not established in the listing.
Variable compensation is mentioned; verify amount, formula, target and eligibility.
Equity or long-term incentive language is mentioned; verify grant type, vesting and valuation basis.
Retirement or pension benefits are mentioned; verify employer contribution and vesting.
Health-benefit language is mentioned; verify coverage, dependants and employee cost.
Paid-leave language is mentioned; verify the exact entitlement and carry-over rules.
A work-arrangement signal is available; verify schedule details before relying on it.
Relocation support not established
Sponsorship not established
A review cycle is mentioned; verify timing and whether compensation can change at that review.
Questions worth taking into the offer conversation
- What is the approved base-pay range for this role?
- Does the package include equity or another long-term incentive, and what are the vesting terms?
- What retirement or pension contribution does the employer provide?
- How much paid leave is provided and what are the carry-over or blackout rules?
- 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?
- What is the approved compensation range, and what portion is guaranteed base pay rather than variable compensation?
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.
European occupation references
This service uses the ESCO classification of the European Commission.
U.S. occupation references
- Data Scientists 15-2051.00
- Computer and Information Research Scientists 15-1221.00
- Social Science Research Assistants 19-4061.00
- Atmospheric and Space Scientists 19-2021.00
- Bioinformatics Scientists 19-1029.01
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
- statistical modeling techniques
- perform project management
- query languages
- online analytical processing
- develop data processing applications
- data engineering
- manage data collection systems
Context-dependent ESCO skills
- manage ICT data architecture
- SPARQL
- use spreadsheets software
- computational biology
- 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.
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
Senior Software Engineer, Product
RevenueCat · EMEA, LATAM, Canada, USA
same seniority band · same employment type · similar work-arrangement evidenceSenior Software Engineer - Infrastructure Security
Quora · Canada, USA
same seniority band · same employment type · similar work-arrangement evidenceSenior Backend Engineer
RevenueCat · EMEA, LATAM, Canada, USA
same seniority band · same employment type · similar work-arrangement evidenceAdjacent-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 Senior / lead. Nearby roles one visible seniority step away can help you judge whether to widen the search, stretch upward or compare the responsibilities more carefully.
Broader-entry direction
Data Scientist: Product
Thatch · Remote — Worldwide
USD 160,000–230,000 / year Similar work arrangement · Same employment type · Recently postedData Engineer Analyst
Blend360 · Remote — Worldwide
Similar work arrangement · Same employment type · Recently postedStretch direction
Director of Product, Machine Learning & Decisioning Platforms
Upstart · Canada, USA
USD 216,100–299,000 / year Similar work arrangement · Same employment type · Recently postedSenior Engineering Manager, Machine Learning
Signifyd · USA
Similar work arrangement · Same employment type · Recently postedThese 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?
Large Language Models is one of the signals this listing shares with skills appearing often across current Data & AI roles opportunities.
Skills named in this listing
Shared with the current career sample
- Large Language Models Seen in 37 sampled listings
- Machine Learning Seen in 45 sampled listings
- Python Seen in 89 sampled listings
Combinations also appearing together
- Machine Learning + Python appeared together in 35 sampled listings
- Large Language Models + Python appeared together in 32 sampled listings
- Large Language Models + Machine Learning appeared together in 20 sampled listings
Application edge
- If these skills match your background, prepare one concrete example that shows how you used Large Language Models, Machine Learning, and Python rather than relying on a keyword-only claim.
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; 115 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.
About 4 years of experience preferred
This is preference evidence, not a mandatory minimum. Prepare examples that demonstrate comparable responsibility rather than assuming the stated number is an automatic rejection threshold.
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.
Machine Learning
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.
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.
Questions worth resolving before you rely on the opportunity
- Compensation: What is the approved compensation range, and what portion is guaranteed base pay rather than variable compensation?
- Application closing time: Is there a firm application deadline, a rolling review window or no stated closing date?
- Work authorization / sponsorship: If sponsorship or work authorization matters to you, what exact immigration or employer-sponsorship conditions apply to this role?
- Application process: What interview, assessment, portfolio, reference or screening stages are part of the hiring process?
Decision analysis
What the listing really tells you
The headline alone does not tell the whole story for Sr. AI/ML Engineer (MXC) at AlertMedia. The clearest decision context comes from work-location flexibility has usable detail, the entry path is becoming clearer, and the visible application effort can be estimated.
Work-location flexibility has usable detail
The work-location pattern is “Limited location freedom”, with Remote Freedom at 53/100. One practical limit to notice is applicant residence or location appears to be restricted..
The entry path is becoming clearer
About 4 years of experience preferred. Only requirements actually stated in the listing are counted; anything left unsaid remains unresolved.
The visible application effort can be estimated
Provider-mediated application path. The external application may contain additional steps that are not visible from the listing itself.
The listing can be traced to a current source
1 recent enabled source can currently renew this vacancy across 1 source classes. That improves traceability, although it does not verify the employer 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?
Comparable salary data is not available for this job yet.
Measures observable location flexibility and explicit restrictions; it does not determine whether remote work is personally desirable.
Missing compensation is not treated as negative evidence; this dimension simply remains unavailable.
The listing was posted about 1 days ago.
At least one enabled source recently observed the vacancy. The source chain is traceable, but this is not independent employer verification.
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
No standout strength is supported strongly enough to list here. That is not a negative rating.
Visible cautions
- Applicant residence or location appears to be restricted.
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.
Pay vs. barriers
Opportunity Efficiency not assessed
The current pay position is not reliable enough to weigh compensation against the stated barriers.
1 explicit Remote Freedom restriction signal is present and is shown separately from qualification requirements.
- Current comparable pay position is unavailable.
- Education requirement 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.
Still check: The current application path is provider-mediated rather than directly classified as an employer-authorized or official route.
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.
Compensation intelligence
How competitive is this pay?
Comparable salary data is not available for this job yet.
Why this analysis?
- Comparable salary data is not available for this job yet.
- Salary confidence: Not available. No disclosed salary can currently be normalized for comparison. Missing compensation is not treated as low-quality salary evidence.
- Range quality: No disclosed range.
Employer compensation communication
Pay transparency at AlertMedia
Limited 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.
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
AlertMedia — current opportunity snapshot
Employer Evidence Profile
How often this employer’s current visible sampled vacancies state decision-critical information. These percentages describe evidence coverage, not employer quality.
Current sampled listings with advertised compensation evidence.
Current sampled listings whose work arrangement is clearer than unknown.
Current sampled listings with a supported country signal.
Current sampled listings with an explicit closing time.
Current sampled listings with a usable posting date.
Current sampled listings that explicitly indicate confirmed, possible or unavailable sponsorship evidence.
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: Customer success (3) · Software engineering (1) · Data & AI (1)
Visible seniority mix: Mid-career (1) · Senior / lead (2) · Leadership (5)
Current employment-type mix: Full time (11)
Most visible hiring countries in this sample: Mexico (5) · United States (4) · Ireland (1)
Other current roles from this employer
Sr. Software Engineer
Mexico
Senior / lead · Remote — restrictions unclearProduct Manager
Remote — Worldwide
Mid-career · Worldwide remoteSenior FP&A Manager
USA
Leadership · Region-restricted remotePartnership Manager
USA
Leadership · Region-restricted remoteThese are other current vacancies visible from the same employer, not endorsements or evidence of future hiring plans.
There are not yet five current disclosed salaries in one currency, so an employer pay median would be too thin to be useful.
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?
- What is the expected application and interview timeline if the listing does not state a closing date?
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
Limited location freedom
Why this score?
- The role is remote, but the exact applicant-location restrictions are not clear.
Location restrictions detected
- Applicant residence or location appears to be restricted.
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.
The available listing details do not contain a clear enough sponsorship statement.
The available listing details do not contain a clear enough relocation statement.
Tradeoff check
What’s the catch?
No obvious trade-off appears in the available job details. That does not mean the role has no drawbacks, so the original listing and employment terms are still worth reading carefully.
Application-path intelligence
What can we see about the application process?
Provider-mediated application path
The current application path comes through a publisher or aggregator. The destination may still lead to an employer-authorized hiring system, but that is not clear enough to assume.
Current destination: jobicy.com · HTTPS
No additional required application step is clear in the available listing text. This does not mean the external application is one-click or friction-free.
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
Basic application-safety context available
The current application destination has a basic transport-safety signal such as HTTPS. This does not verify the employer, vacancy, recruiter or application process.
Evidence checked: Source provenance · Application destination · Listing wording
Observable transport-safety signals
- The available application destination uses HTTPS.
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.
Do work that matters.
At AlertMedia, we help organizations protect their people, operations, and brand. Our modern Risk Intelligence and Response platform empowers teams to detect emerging threats, assess impact, and respond with confidence. We believe building resilience should be simpler—and it starts with bringing critical information and workflows together in one unified platform.
Our core values drive us in our important mission of keeping people safe & informed:
- We’re humans not robots
- Customers always come first
- We work better together
- Simplicity is our strength
- Our reputation is priceless
- Hard work pays off
AlertMedia is looking for an innovative and hands-on Sr. AI/ML Engineer with a strong background in applied machine learning and data science to lead the evaluation, training, and integration of advanced AI and machine learning models across our product suite. In this role, you will help shape our AI strategy by identifying the most appropriate models for our use cases, optimizing their performance through fine-tuning and prompt engineering, and ensuring their responsible deployment within our platforms. You will have the opportunity to show who you are throughout our interview process; we don’t ask any trick questions or expect you to perform a whiteboard exercise. We want to see you shine by showing us work you are most proud of!
Who you are:
You are an applied AI and machine learning engineer with strong data science fundamentals, deeply curious about what's possible with large language models and practical machine learning applications. You’re a collaborative engineer who thrives in a fast-moving environment, and you’re as comfortable training and fine-tuning models as you are crafting prompts or evaluating model outputs. You have a strong understanding of ML fundamentals, but you're pragmatic in applying the right solution for the problem.
What you get to do every day:
- Train and fine-tune supervised learning models (e.g., classification, ranking, embeddings) for internal tools and customer-facing product features.
- Lead prompt engineering and testing efforts to fine-tune LLM behavior for specific use cases across the product suite.
- Design and implement evaluation pipelines for both LLMs and traditional ML models.
- Work with and optimize Elasticsearch-backed data systems that power AI and intelligence pipelines.
- Proactively identify opportunities to improve AI models, data pipelines, and engineering workflows beyond the existing roadmap.
- Develop tools and frameworks to support prompt iteration, model benchmarking, and performance tracking.
- Coordinate with security team to ensure adherence to AI compliance standards.
- Evaluate and compare commercial and open-source LLMs (e.g., OpenAI, Anthropic, Mistral, Meta, etc.) for performance, cost, alignment, and reliability.
- Collaborate with product and engineering teams to integrate AI features in a safe, scalable, and maintainable way.
- Monitor, evaluate, and continuously improve the performance of AI and machine learning models in production.
- Stay informed of emerging research in NLP, machine learning, and AI infrastructure, and evaluate potential applications for the business.
- Contribute to AlertMedia’s culture, values and vision for the future.
What you bring to the role:
- Bachelor’s degree in a technical field such as computer science, computer engineering or related field preferred.
- 5+ years of software engineering experience, Python preferred.
- 4+ years of experience in data science and/or software engineering, specifically in machine learning engineering, or applied AI.
- Strong understanding of LLMs and traditional machine learning methods.
- Experience with prompt engineering, model fine-tuning, and evaluation.
- Familiarity with model evaluation best practices, including offline metrics, cross-validation, and A/B testing.
- Proficiency in Python and ML libraries (e.g., scikit-learn, PyTorch, TensorFlow, Hugging Face).
- Experience working with Elasticsearch or other large-scale search and indexing platforms.
- Experience with cloud-based ML tooling (e.g., SageMaker, Bedrock) and data workflows.
- Demonstrated experience training and deploying supervised learning models, ideally in production environments (a plus).
- Ability to work independently and collaboratively on cross-functional teams.
- Strong organizational skills and ability to manage working on multiple projects in parallel.
- The ability and desire to work in a fast-paced challenging environment.
Location: This position is remote based in Mexico. Must reside in Mexico and we have an office in Mexico City (Reforma area), if you're interested in going into the office. Not required, but optional.
Sponsorship: AlertMedia does not sponsor employment visas. Candidates must have existing authorization to work in Mexico without the need for sponsorship now or in the future.
Identity Verification: To protect our candidates and our company from hiring fraud, finalists may be asked to complete an identity verification and present valid government-issued identification before or during the hiring process. By applying, you acknowledge that all interviews and assessments must be completed by you and not by another individual acting on your behalf.
Why you’ll love working at AlertMedia:
At AlertMedia, you won’t just build your career — you’ll be part of something meaningful, surrounded by people who genuinely care about the work and each other.
- Competitive Base Salary (Bi-Monthly payroll)
- Annual Company Bonus
- 100% Employer-Paid Medical, Dental, and Vision Coverage
- Parental Leave Program
- Christmas Bonus (Aguinaldo)
- Generous Vacation and Holiday Policy
- Additional Vacation Bonus
- Monthly Work-from-Home Stipend
- All Necessary Equipment Provided: Laptop, monitor and accessories
- Recognition & Rewards: We celebrate wins big and small
- Language Immersion Program with employees spread out across the globe (English, Spanish, etc...depending on your interest)
- Continuous Learning & Growth: From mentorship and tech talks to personalized 1:1 career development sessions, we’re deeply committed to investing in your professional journey
- Award Winning Culture: We're proud to be recognized as a BEST WORKPLACE FOR 10 YEARS IN A ROW
- The Work & People: We’re passionate about the meaningful work we do—and even more grateful for the incredible people we get to do it with!
About AlertMedia:
We are the leading risk intelligence and response platform — trusted by the largest companies in the world to protect their people and assets when it matters most. We are a high-growth, PE-backed SaaS company with more than 4,000 clients scaling rapidly across the globe. Our technology is unmatched with a unified platform, a 7+year history of AI innovation, a customer NPS of 70+, and a culture that sets us even further apart from our competition.
We are an equal opportunity employer focused on creating a collaborative and exciting place for all to work. Ensuring a diverse, inclusive, and equitable workplace for all people is key to our success and core to our values. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
This is an amazing opportunity to be part of our wave of momentum and take our company, and your career, to the next growth stage. We'd love to get to know you better and share how we serve our amazing customers. For more information, please visit www.alertmedia.com.
Come join us in our mission to save lives and minimize loss through effective communication.
By applying for the role, you agree that AlertMedia will use your Personal Information in connection with the recruitment process and in accordance with our Privacy Policy – https://www.alertmedia.com/legal/privacy-policy/
Listing provenance
Where did this job come from?
See where this vacancy came from and whether more than one current source can still support it. Source names help with traceability and attribution; they are not endorsements or guarantees.
At least one enabled source recently observed the vacancy. The source chain is traceable, but this is not independent employer verification.
- Continuity
- One recent renewable source
- Source-class independence
- One renewable source class
- Last source observation
- Observed today
This records when High Paid Job last observed the vacancy in source evidence. It confirms source presence, not that the employer edited the vacancy at that time.
- 1 enabled source recently observed this vacancy.
Source confidence is about traceability and continuity. It is separate from application safety and should not be read as an employer reputation rating.
The vacancy is supplied by an external job publisher. Source information helps show where the listing came from; it is not a guarantee about the employer or vacancy.
Listing source: Jobicy. Destination: jobicy.com. The application opens in a new tab so you can keep this report open.