Job intelligence
Principal Machine Learning Engineer (Memory & Context)
Zillow Group
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
The strongest upside: pay compares strongly with similar current roles. The main trade-off: the experience requirement raises the entry bar.
Around the 91th percentile within 64 comparable USD salary observations.
No material geography, office-attendance or timezone restriction is visible in the available wording.
One or more material qualification requirements are stated and may narrow the realistic applicant pool.
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
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
- Location eligibility
- 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.
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
- Pay compares strongly with similar current roles: The annualized midpoint is around the 91th percentile among 64 comparable USD salary observations.
- 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 experience requirement raises the entry bar: The listing appears to require at least about 5 years of experience.
Questions worth asking before you invest more time
- 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.
Machine Learning Infrastructure Engineer
Bright Vision Technologies · Remote — Worldwide
Why it is nearby: Same seniority band · Similar work arrangement · Same employment type
About 54% lower advertised midpoint
Sr. Data Analytics Engineer (R14153)
Oportun · Anywhere in the World
Why it is nearby: Same seniority band · Similar work arrangement · Same employment type
Senior Data Analyst
ShopFully · Italy
Why it is nearby: Same seniority band · Similar work arrangement · Same employment type
Senior Machine Learning Engineer
Faculty · London
Why it is nearby: Same seniority band · Same employment type · Recently posted
Different angle: 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 (23) · EUR (5) · GBP (5) · CAD (3). 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.
Counts only affirmative or possible sponsorship evidence, or relocation explicitly offered. Unknown is not treated as no.
Only same-currency opportunities with usable annualized pay enter this comparison. Other currencies are not converted or treated as lower.
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 979 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 18% of the bounded current role sample does the same.
Compensation counts only when amount, ISO currency and supported pay period are all known.
Pay disclosure is uncommon in the current role sample.
Employer-level comparison is withheld until enough current employer listings are available.
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: 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.
Usable advertised compensation is available.
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
- Is there a bonus, commission or other variable-pay component, and how is it calculated?
- What retirement or pension contribution does the employer provide?
- What health coverage is included and what costs remain with the employee?
- 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?
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
- ProgrammingPhrase in listing
- 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 Product Design Manager, Payroll
Gusto, Inc. · Anywhere in the World
same seniority band · same employment type · similar work-arrangement evidenceLead Product Management
Carrot · Anywhere in the World
same seniority band · same employment type · similar work-arrangement evidenceSenior Software Engineer (R14285)
Oportun · Anywhere in the World
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 Engineer Analyst
Blend360 · Remote — Worldwide
Similar work arrangement · Same employment type · Recently postedData Engineer
DIGITALL Nature Corp · Remote — Worldwide
Similar work arrangement · Same employment type · Recently postedStretch direction
Principal Data Scientist - R01568403
Brillio · Remote — Worldwide
USD 180,000–190,000 / year Similar work arrangement · Same employment type · Recently posted Advertised midpoint is about 31% lowerSr. Data Engineer
Carrot · USA
USD 145,000–165,000 / year Similar work arrangement · Same employment type · Recently posted Advertised midpoint is about 42% lowerThese 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 38 sampled listings
- Machine Learning Seen in 43 sampled listings
- Python Seen in 90 sampled listings
Combinations also appearing together
- Machine Learning + Python appeared together in 36 sampled listings
- Large Language Models + Python appeared together in 33 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.
- The listing states about 5 years of required experience. Check that the dates and scope in your application make that experience easy to verify.
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.
At least about 5 years of experience required
The available wording contains an explicit minimum/required years-of-experience signal. Preferred years are tracked separately and never promoted into the required minimum.
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
- 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 Principal Machine Learning Engineer (Memory & Context) at Zillow Group. The clearest decision context comes from compensation has enough depth for comparison, the location rules are clear enough to judge, and the listing gives useful clues about who can realistically enter.
Compensation has enough depth for comparison
The annualized midpoint sits near the 91th percentile within 64 comparable USD salary observations. Treat that as current advertised-pay context rather than a forecast of take-home or total compensation.
The location rules are clear enough to judge
The work-location pattern is “Highly location-flexible”, with Remote Freedom at 100/100.
The listing gives useful clues about who can realistically enter
At least about 5 years of experience required · 1 additional stated barrier. Unstated education or experience requirements stay open rather than being assumed.
The application route gives a few useful clues
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
Built from the pay, location, qualification, mobility, application and source details available for this vacancy. Anything the listing leaves unresolved stays unresolved.
Analysis evidence coverage
How much analysis can the current evidence support?
Uses the explainable High Pay Score within the job’s current occupation/seniority/currency comparison sample.
Measures observable location flexibility and explicit restrictions; it does not determine whether remote work is personally desirable.
The salary is source-provided and normalizable, but the advertised range is broad enough to reduce comparison precision.
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
- Advertised pay is above much of the current comparable disclosed-salary sample.
- The available work-location evidence indicates strong location flexibility.
Visible cautions
- The description appears to mention an advanced degree requirement or preference.
- At least about 5 years of experience required
Still unknown
- Visa sponsorship is not established by the available listing data.
Pay vs. barriers
Strong pay with stated barriers to weigh
Pay compares strongly, but qualification or location constraints are also visible. Higher pay does not erase those practical requirements.
Comparable disclosed-pay evidence places this job at about 91 / 100 within its current occupation/seniority sample.
1 explicit required barrier is visible in the available wording.
The listing states at least about 5 years of required experience.
- 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
Strong multidimensional signals
The role combines a strong current pay position with at least one clear non-pay advantage. Whether that makes it a better choice depends on your priorities.
The annualized salary midpoint is at or above about 91% of the current comparable disclosed-salary sample.
The observable Remote Freedom evidence is strong and contains few explicit restriction signals.
Still check: At least about 5 years of experience required · 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.
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.
Its annualized salary midpoint is at or above about 91% of the current comparable disclosed-salary sample.
The observable work-location signals indicate unusually strong location flexibility.
The listing was posted about 1 days ago.
Compensation intelligence
How competitive is this pay?
Exceptional pay in current sample
The annualized midpoint is above the 75th percentile boundary of the current comparable sample.
The highlighted band is the middle 50% of the current comparable sample after the outlier guard. The dark marker is this job’s annualized salary midpoint.
Why this analysis?
- This score reflects the current advertised-pay distribution for comparable active jobs in the same currency. It measures pay position, not overall job quality.
- Salary confidence: Medium. The salary is source-provided and normalizable, but the advertised range is broad enough to reduce comparison precision.
- Range quality: Broad but usable range.
Employer compensation communication
Pay transparency at Zillow Group
Only 1 current listing from this employer is indexed. At least three are required before employer-level pay transparency is summarized.
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
Zillow Group — current opportunity snapshot
Only 1 current listing from this employer is visible. At least three are needed before an employer pattern is shown.
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
Highly location-flexible
Why this score?
- The source describes the role as open worldwide or globally.
Flexibility signals detected
- Worldwide or global remote eligibility is explicitly indicated.
- The description reinforces broad location independence.
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?
These are visible conditions worth checking before treating the headline compensation as the whole story:
- The description appears to mention an advanced degree requirement or preference.
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.
Engineering Manager, Machine Learning (Safety)
Discord · USA
USD 272,000–340,000 / year Region-restricted remoteWhy comparable: Same seniority band · Similar work-location arrangement · Same employment type
Ads Conversion Modeling, Machine Learning Engineering Manager
Reddit · USA
USD 230,000–322,000 / year Region-restricted remoteWhy comparable: Same seniority band · Similar work-location arrangement · Same employment type
Staff AI Engineer - AI Product
ClickUp · USA
USD 250,000–300,000 / year Region-restricted remoteWhy comparable: Same seniority band · Similar work-location arrangement · Same employment type
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?
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: himalayas.app · 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.
About the team
The Agentic AI team at Zillow is at the forefront of transforming the real estate industry by helping millions of people use AI assistants to find their next home. We aim to redefine the home shopping and transaction experience by providing an always-on assistant that integrates personalized user insights with Zillow's knowledge. Within this organization, our team owns how the assistant remembers and understands each user across a home search that can last for months: agent memory, context engineering, and the evaluation of agents running in production. We are a senior, fast-moving team of machine learning engineers who do the science and own taking it to production.About the role
As a Principal Machine Learning Engineer on the Agentic AI team, you will get to:
- Own the architecture of agent memory: what Zillow's assistant remembers about each user across conversations, and how memories are written, retrieved, updated, and retired
- Lead context engineering for production agents: assembling, prioritizing, and compressing context from conversation history, user memory, tools, and skills so every response is relevant, fast, and cost-efficient
- Build and orchestrate agents end to end, from prompt and context design to deployment and operation in production
- Define evaluation frameworks for memory and context quality, offline and online, and use them to drive product and technical decisions
- Stay on the cutting edge of emerging agentic paradigms, including memory architectures and long-context techniques, and convert them into tangible product innovation
- Lead complex, multi-team initiatives and communicate technical direction clearly to engineers, partner teams, and leadership
Who you are
You are a hands-on technical leader with high agency: when a problem is ambiguous or blocked, you go talk to the people who can solve it, and you make your work visible.
Must-haves
- A master's degree or above, or equivalent experience, in Computer Science, Electrical Engineering, or a related field
- 5+ years of experience deploying large-scale ML systems, including at least the most recent year building and shipping LLM-based agents in production
- Hands-on experience building agents end to end: orchestration, prompt engineering and optimization, and context engineering
- Experience evaluating agentic systems and using those results to improve them
- Proven technical leadership: you have influenced technical direction across teams and mentored other engineers
- Strong communication skills, including presenting to senior leadership
- Strong programming skills in Python and familiarity with agentic AI frameworks such as LangGraph, Agents SDK, or AutoGen
Nice-to-haves
- Experience designing agent or user memory systems (long-term, episodic, or user-profile memory)
- Experience with dialogue systems that sustain long, multi-session conversations
- Personalization of AI assistants from conversation history
- Publications, patents, or open-source contributions related to memory, long-context models, or agents
Get to know us
At Zillow, we’re reimagining how people move—through the real estate market and through their careers. As the most-visited real estate platform in the U.S., we help people navigate buying, selling, financing and renting with greater ease and confidence. Whether you're working in tech, sales, operations, or design, you’ll be part of a company reshaping an industry and helping more people make home a reality.
How we work is a key part of that transformation. Through Cloud HQ, our strategic approach to distributed work, most employees have the flexibility to work from wherever they’re most productive—enabling us to move fast, stay connected and deliver on our people promise.
Zillow is honored to be recognized among the best workplaces in the U.S. Zillow was named one of FORTUNE 100 Best Companies to Work For® in 2026, and included on TIME’s America’s Best Companies 2026 list, reflecting our commitment to creating an innovative, inclusive, and engaging culture where employees are empowered to grow.
No matter where you sit in the organization, your work will help drive innovation, support our customers, and move the industry—and your career—forward, together.
Zillow Group is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please contact your recruiter directly.
Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable state and local law.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Originally posted on Himalayas
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 in the past 3 days
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: Himalayas. Destination: himalayas.app. The application opens in a new tab so you can keep this report open.