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advisor - scientific data engineer Jobs in San Francisco

advisor - scientific data engineer

ai engineer, ai & data platforms (aidp) Jobs in San Francisco

ai engineer, ai & data platforms (aidp)

advisor scientific data engineer

Eli Lilly

<div>At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We&rsquo;re looking for people who are determined to make life better for people around the world.<h1 class="jobSectionHeader">
The Opportunity</h1>
We are building something unprecedented &mdash; an AI foundation that will push the frontier on what is possible today across drug discovery research, from target identification and disease biology through translational science.
The Applied Intelligence for Discovery (AI4D) team is a newly formed group within Lilly Research Laboratories that operates at the intersection of scientific delivery and core platform development. AI4D&rsquo;s mission is connecting scientists to petabyte-scale data through natural language interfaces, automated analysis workflows, and intelligent search &mdash; and to convert early deployments into repeatable system standards and evaluation practices that scale across therapeutic areas.
As a Scientific Data Engineer, you will close that gap. You will build the semantic layer, data harmonization infrastructure, AI-ready data products, and lakehouse architecture that bridge how data is stored and how AI systems need to consume it. You will be working at the intersection of the data infrastructure team and the generative AI engineers who build the systems scientists interact with.<h1 class="jobSectionHeader">
Responsibilities</h1><h2 class="jobSectionHeader">
Data Harmonization and Lakehouse Architecture</h2><ul><li>
Design and build the data architecture that transforms raw and processed omics data into harmonized, AI-consumable layers</li><li>
Build and optimize ETL/ELT pipelines that produce denormalized views, pre-computed aggregations, embedding-ready text representations, and feature stores optimized for AI system consumption</li><li>
Implement data quality monitoring, automated profiling, and validation checks across harmonization layers</li><li>
Create versioned, reproducible data snapshots that support model training, evaluation, and audit requirements in a regulated environment</li><li>
Partner with the teams to extend harmonization patterns as data modalities expand beyond genomics and proteomics into spatial transcriptomics, perturbational data (Perturb-Seq), single-cell, and digital pathology</li></ul><h2 class="jobSectionHeader">
Semantic Layer and Schema Engineering</h2><ul><li>
Design and maintain a semantic layer over Lilly&rsquo;s multi-omics databases that enables AI systems</li><li>
Create comprehensive schema documentation: table descriptions, column-level annotations, relationship mappings, business logic rules, and domain-specific constraints (e.g., statistical thresholds, unit conventions, experimental design metadata)</li><li>
Develop gold-standard question/SQL pairs for each major database, in collaboration with computational biologists and Generative AI Engineers, to serve as training data, few-shot examples, and evaluation benchmarks</li><li>
Build and maintain a data dictionary and ontology mapping layer that translates how scientists think and speak about data (gene names, pathway terms, assay types) into how the data is physically stored</li></ul><h2 class="jobSectionHeader">
AI-Ready Data Products</h2><ul><li>
Build and manage vector embedding pipelines for scientific documents, study metadata, and structured data descriptions to power RAG-based retrieval</li><li>
Build integration pipelines that connect heterogeneous data sources &mdash; omics databases, internal publications, electronic lab notebooks, assay results, and clinical annotations &mdash; into a unified, queryable layer</li><li>
Develop and enforce metadata standards that ensure new data sources are AI-accessible from the point of ingestion, not retroactively</li><li>
Design data products that serve multiple consumption patterns: direct SQL access for computational biologists, structured feeds for ML training pipelines, and semantic interfaces for LLM-powered tools</li></ul><h1 class="jobSectionHeader">
Qualifications</h1><ul><li>
Bachelors degree in Computer Science, Data Engineering, Bioinformatics, or a related field + 8 years data engineering experience OR Masters degree and 5 years data engineering experience</li><li>
Demonstrated expertise in building data pipelines, ETL/ELT workflows, and data products that serve downstream AI/ML systems</li></ul><h1 class="jobSectionHeader">
Additional Skills/Preferences</h1><ul><li>
Phd in data or related field</li><li>
Strong SQL skills and experience with complex relational database schemas (hundreds of tables, multi-level joins, domain-specific conventions)</li><li>
Experience with modern data platform technologies, including at least one of: Databricks, Snowflake, or equivalent lakehouse platforms</li><li>
Experience with modern data engineering tools: dbt, Spark, Airflow, or similar orchestration and transformation frameworks</li><li>
Proficiency in Python for data processing, scripting, and pipeline development</li><li>
Experience with cloud data platforms (AWS preferred: Redshift, Athena, Glue, S3, or similar)</li><li>
Familiarity with at least one of: vector databases, embedding pipelines, or semantic layer tooling</li><li>
Strong communication skills &mdash; you can work effectively with both engineers who think in schemas and scientists who think in biology</li><li>
Experience with biomedical or scientific data: omics datasets (RNA-seq, proteomics, GWAS), clinical data, or laboratory information management systems</li><li>
Experience in pharmaceutical, biotech, or life sciences environments</li></ul><ul><li>
Familiarity with biomedical ontologies and controlled vocabularies (Gene Ontology, MeSH, ChEBI, HGNC) and their application to data integration</li><li>
Experience building data products that serve AI/ML systems &mdash; feature stores, training datasets, evaluation benchmarks, or semantic annotations for text-to-SQL</li><li>
Knowledge of data governance practices in regulated industries: data lineage, access controls, versioning, and auditability</li><li>
Experience with knowledge graph technologies (Neo4j, Amazon Neptune, RDF/SPARQL) or graph-based data modeling</li><li>
Deep experience with Databricks ecosystem: Unity Catalog for data governance, Delta Lake for ACID transactions, MLflow integration, and Databricks SQL for analytics workloads</li><li>
Experience designing data architectures that bridge traditional bioinformatics workflows (Nextflow, R/Bioconductor) with modern lakehouse consumption patterns</li></ul>
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status. 
Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women&rsquo;s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.
Actual compensation will depend on a candidate&rsquo;s education, experience, skills, and geographic location. The anticipated wage for this position is
$166,500 - $266,200
Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly&rsquo;s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.
#WeAreLilly</div>

Advisor - Scientific Data Engineer

Prolific

<div>
 AI Trainer - Neuroscience Specialist (Remote Advisory)
 
 
 
 About Prolific
 
 
 
 Prolific is not just another player in the AI space &ndash; we are building the biggest pool of quality human data in the world.
 
 
 Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.
 
 
 
 The role
 
 
 
 We are seeking
 
 Neuroscience Experts
 
 to act as evaluators for a high-level AI verification project. AI models are now generating complex technical summaries, and we need specialists to ensure these outputs maintain scientific integrity and factual accuracy.
 
 
 We need experts who can navigate dense scientific literature to judge the accuracy and structural integrity of AI-generated graphical abstracts. This is a flexible, ad hoc project paying
 
 $40+/h
 
 where your technical expertise directly influences how AI understands and summarizes complex research.
 
 
 
 What you'll bring
 
 
 
 <ul>
 <li>
 Specialized knowledge: Deep expertise in Neuroscience
 </li>
 <li>
 Advanced Academic Credentials: you must hold a Master's or PhD in Neuroscience or a related field.
 </li>
 <li>
 Analytical Skills: history with fact-checking tasks and strong attention to detail
 </li>
 <li>
 Nice to have: Previous experience with AI-related training or evaluation tasks and a background in scientific publishing or peer review.
 
 
 </li>
 </ul>
 
 What you'll be doing in the role
 
 
 
 <ul>
 <li>
 
 Scientific Review:
 
 review scientific papers alongside LLM-generated graphical abstracts.
 </li>
 <li>
 
 Fact-Checking:
 
 identify issues and inaccuracies where the graphical abstract does not faithfully represent the source scientific paper.
 </li>
 <li>
 
 Expert Verification:
 
 use your domain knowledge to ensure that technical concepts are visually and textually summarized correctly.
 
 
 </li>
 </ul>
 
 Please note that to qualify for this study you will be required to pass a paid skills assessment with a sample paper and graphical abstract
 
 
 
 
 Why Prolific is a great platform to join as a Participant
 
 
 
 Joining our platform as a Prolific participant will give you the chance to influence the AI models of the future using professional legal expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home.
 
 
 We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.
 
 
 We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation &ndash; one that reflects the breadth and the best of humanity.
 
 
 
 Links to more information on Prolific
 
 
 
 Website
 
 
 Youtube
 
 
 
 Privacy Statement
 
 
 
 By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.
</div>

AI Trainer - Neuroscience (Fully Remote- San Francisco)

Apple

Apple Services Engineering (ASE) powers many AI features across App Store, Music, Video and more. We build deeply personal products with the goal of representing users around the globe authentically. We work continuously to avoid perpetuating systemic biases and maintain safe and trustworthy experiences across our AI tools and models. 
 
Description 
 
Our team, part of Apple Services Engineering, is looking for an ML Research Engineer to lead the design and continuous development of automated safety benchmarking methodologies. In this role, you will investigate how media-related agents behave, develop rigorous evaluation frameworks and techniques, and establish scientific standards for assessing risks they pose and safety performance. This role supports the development of scalable evaluation techniques that ensure our engineers have the right tools to assess candidate models and product features for responsible and safe performance. 
 
The capabilities you build will allow for the generation of benchmark datasets and evaluation methodologies for model and application outputs, at scale, to enable engineering teams to translate safety insights into actionable engineering and product improvements. This role blends deep technical expertise with strong analytical judgment to develop tools and capabilities for assessing and improving the behavior of advanced AI/ML models. You will work cross-functionally with Engineering and Project Managers, Product, and Governance teams to develop a suite of technologies to ensure that AI experiences are reliable, safe, and aligned with human expectations. 
 
The successful candidate will take a proactive approach to working independently and collaboratively on a wide range of projects. In this role, you will work alongside a small but impactful team, collaborating with ML and data scientists, software developers, project managers, and other teams at Apple to understand requirements and translate them into scalable, reliable, and efficient evaluation frameworks.&quot;,&quot;responsibilities&quot;:&quot;Design scientifically-grounded benchmarking methodologies covering multiple dimensions of responsibility and safety across several media and application marketplace use cases 
 
Develop automated evaluation pipelines that collect, automatically judge, and analyze model outputs with respect to safety policies, at scale 
 
Create and curate datasets, tasks, and feature usage scenarios that represent realistic and adversarial use cases across multiple languages, markets, and domains 
 
Define and validate new metrics for complex phenomena such as multi-turn agentic interaction patterns 
 
Apply statistical rigor and reproducibility to above mentioned objectives 
 
Work closely with engineering and research teams to translate experimental findings into actionable model improvements and safety mitigations 
 
Publish internal reports and external papers 
 
Monitor evolving industry practices and academic work to ensure benchmarks remain relevant 
 
Preferred Qualifications 
 
Publications in AI/ML evaluation or related fields 
 
Experience with automated testing frameworks 
 
Experience constructing human-in-the-loop or multi-turn evaluation setups 
 
Intermediate or Advanced Proficiency in Swift 
 
Familiarity with RAG systems, reinforcement learning, agentic architectures, and model fine-tuning 
 
Expertise in designing annotation guidelines and validation instruments and techniques 
 
Background in human factors, social science, and/or safety assessment methodologies 
 
Minimum Qualifications 
 
Advanced degree (MS or PhD) in Computer Science, Software Engineering, or equivalent research/work experience 
 
1+ years of work experience either as a postdoc or in the industry 
 
Strong research background in empirical evaluation, experimental design, or benchmarking 
 
Strong proficiency in Python (pandas, NumPy, Jupyter, PyTorch, etc.) 
 
Deep familiarity with software engineering workflows and developer tools 
 
Experience working with or evaluating AI/ML models, preferably LLMs or program synthesis systems 
 
Strong analytical and communication skills, including the ability to write clear reports 
 
Technical Skills: 
 
Proficiency in Python (pandas, NumPy, Jupyter, PyTorch, etc.). 
 
Experience working with large datasets, annotation tools, and model evaluation pipelines 
 
Familiarity with evaluations specific to responsible AI and safety, hallucination detection, and/or model alignment concerns 
 
Ability to design taxonomies, categorization schemes, and structured labeling frameworks 
 
Analytical Strength: Ability to interpret unstructured data (text, transcripts, user sessions) and derive meaningful insights 
 
Communication: Strong ability to stitch together qualitative and quantitative insights into actionable guidance; strong ability to communicate complex architectures and systems to a variety of stakeholders 
 
Education in Data Science, Linguistics, Cognitive Science, HCI, Psychology, Social Science, or a related field 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

ML Safety Engineer, ASE

AbbVie

<div>
 
 Company Description
 
 
 
 
 About AbbVie
 
 
 
 AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.
 
 
 
 Job Description
 
 
 
 
 These positions are field based / remote in the following locations: CA, WA, OR, IA, MN, IN, OH, FL. Candidates must reside in one of the these states and be willing to travel for site visits.
 
 
 
 
 Purpose
 
 
 
 Advance AbbVie's pipeline by striving for excellence in clinical research, turning science into medicine for our patients and leveraging new advanced capabilities to drive industry leading performance.
 
 
 Partners with the investigator and site staff for meaningful and effective engagements positioning AbbVie as the choice in clinical trials.
 
 
 Focus on site clinical research that ensures appropriate conduct of the trial while driving improvement in data integrity, compliance, overall study performance and customer experience.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Considered as the primary point of contact for the investigative site. High level of competency or experience in providing contextual information on the clinical trials, connects stakeholder to the investigative sites and strengthens AbbVie&rsquo;s positioning.
 </li>
 <li>
 Aligns, trains and motivates the site staff and principal investigator on the goals of the clinical trial program, protocol and patient treatment principles for the trial ensuring a trusted partnership.
 </li>
 <li>
 Conducts site evaluation, site training, routine, and site closure monitoring activities with compliance to the protocol and monitoring plans, in accordance with applicable regulations, Good Clinical Practices (GCPs), ICH Guidelines, AbbVie Standard Operating Procedures (SOPs), and quality standards, ensuring safety and protection of study subjects.
 </li>
 <li>
 Advanced understanding of site engagement and ability to customize site engagement strategy for assigned study (ies). Gather local/site insights and utilize site engagement tools such as the Customer Relationship Management (CRM) tool, to report/track progress and measure impact of that strategy.
 </li>
 <li>
 Advanced level of competency connecting the study protocol, scientific principles and clinical trial requirements to the day-to-day clinical trial execution activities. Evaluate and ensure effective recruitment and retention techniques/plans based on the patient disease journey. Develop solid knowledge of therapeutic area, asset and clinical landscape / patient journey to enable successful patient recruitment and overall protocol compliance.
 </li>
 <li>
 Possesses experienced level of competency to mentor and train less experienced CRAs on various aspects of work and provides input into their development. May participate in global/local task forces and initiatives. Responsible for activities as assigned by manager.
 </li>
 <li>
 Responsible for continuous risk-assessment proactively, and in collaboration with Central Monitoring team, monitor activities conducted by clinical sites to detect early overall study performance or patient safety issues.
 </li>
 <li>
 Advanced ability to think critically to resolve site risk signals while having robust understanding of site processes to drive study execution. Ensures preventative and corrective action plans are put into place, as needed, to mitigate risk and promote compliance using a customer centric approach.
 </li>
 <li>
 Identifies, evaluates and recommends new/potential investigators/sites on an on going basis. Potential sites may be identified through networking or internal AbbVie requests to assist in the placement of planned clinical studies with qualified investigators.
 </li>
 <li>
 Ensures quality of data submitted from study sites and assures timely submission of data, including appropriate reporting and follow-up for all safety events by site personnel. Ensures audit and regulatory inspection readiness at assigned clinical site at all times. Manages investigator payments as per executed contract obligations, as applicable.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Qualifications
 
 
 
 <ul>
 <li>
 Education: Bachelor&rsquo;s degree or equivalent degree; health related preferred (e.g. Medical, Scientific, Nursing, Pharmacy).
 </li>
 <li>
 Minimum of 1 year of clinically related experience, of which a period of 6 months is required in clinical research monitoring of investigational drug or device trials. Familiar with risk&hyphen;based monitoring approach, onsite and offsite monitoring.
 </li>
 <li>
 Knowledge of appropriate therapeutic area indications is preferred with the ability to understand and apply scientific concepts as they relate to the conduct of clinical trials.
 </li>
 <li>
 Advanced knowledge on existing and emerging local regulatory and legal requirements, ICH/GCP Guidelines and applicable policies.
 </li>
 <li>
 Demonstrate strong cross-functional collaboration skills among internal and external stakeholders.
 </li>
 <li>
 Demonstrate strong planning and organizational skills and the ability to work effectively and efficiently in a dynamic environment with competing projects and deadlines.
 </li>
 <li>
 Advanced ability to leverage technology, tools and resources to provide customer centric support based on the health of the site.
 </li>
 <li>
 Strong interpersonal skills with excellent written, verbal, active listening and presentation skills, with ability to establish and leverage site relationships and trusted partnerships through engagement, motivation, and training.
 </li>
 <li>
 Ability to use functional expertise with appropriate guidance, leverage critical thinking skills and apply good judgement to address clinical site issues.
 </li>
 <li>
 Acts with integrity in accordance with AbbVie code of business conduct and leadership values. Self-motivated individual focused on delivering timely and quality outcomes in a fast-paced environment.
 
 
 </li>
 </ul>
 Additional Information
 
 
 Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
 
 
 <ul>
 <li>
 The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role atthe time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors includinggeographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.
 </li>
 <li>
 We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
 </li>
 <li>
 This job is eligible to participate in our short-term incentive programs.
 
 
 </li>
 </ul>
 Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested,and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to aparticular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company&rsquo;s sole and absolute discretion,consistent with applicable law.
 
 
 AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community.  Equal Opportunity Employer/Veterans/Disabled.
 
 
 US &amp; Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html
 
 
 US &amp; Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:
 
 
 https://www.abbvie.com/join-us/reasonable-accommodations.html
</div>

Clinical Research Associate II - Oncology (Remote US - Multiple Openings)

ICON Consultants, LP

<div>
 
 
 Recruiter I (High-Volume) &ndash; Contract
 
 
 
 
 Location:
 
 Remote (U.S. &amp; Canada)
 
 
 
 Pay Rate:
 
 $35.00 &ndash; $40.00/hr
 
 
 
 Duration:
 
 Contract
 
 
 
 Overview
 
 
 
 We are seeking a high-volume
 
 Recruiter I
 
 to support a fast-paced Community Operations organization across the U.S. and Canada. This role partners closely with business leaders to execute scalable hiring strategies and deliver top talent in a high-volume, non-technical environment.
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Manage full-cycle, high-volume recruiting across multiple requisitions
 </li>
 <li>
 Partner with Hiring Managers and stakeholders to drive alignment across the hiring process (intake, sourcing, interview flow)
 </li>
 <li>
 Act as a trusted advisor to the business, providing market insight and hiring strategy recommendations
 </li>
 <li>
 Track and analyze recruiting metrics (time in stage, conversion rates, offers) to improve performance
 </li>
 <li>
 Maintain a strong candidate experience through consistent communication and expectation management
 </li>
 <li>
 Collaborate with hiring teams to refine job descriptions and optimize hiring processes
 </li>
 </ul>
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 2+ years of full-cycle, high-volume recruiting experience (non-technical)
 </li>
 <li>
 Proven track record of meeting or exceeding monthly/quarterly recruiting KPIs
 </li>
 <li>
 Strong stakeholder management and communication skills
 </li>
 <li>
 Ability to manage multiple requisitions in a fast-paced environment
 </li>
 </ul>
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Business, Human Resources, Communications, or related field
 </li>
 <li>
 Experience working with ATS platforms (ICIMS or similar)
 </li>
 <li>
 Experience partnering with senior-level stakeholders
 </li>
 <li>
 Data-driven approach to recruiting and decision-making
 </li>
 </ul>
 
 
 Core Competencies
 
 
 <ul>
 <li>
 
 Business Acumen:
 
 Acts as a Subject Matter Expert, confidently advising and guiding Hiring Managers
 </li>
 <li>
 
 Operational Agility:
 
 Thrives in a fast-paced, high-volume environment with strong problem-solving skills
 </li>
 <li>
 
 Autonomy:
 
 Highly organized self-starter with the ability to manage workload independently
 </li>
 </ul>
 
 
</div>

Recruiter

POLYMATH

<div>About Polymath
Polymath is an applied research lab focused on advancing long-horizon agent capabilities through reinforcement learning. We design and scale simulation environments where agents learn to operate safely and autonomously. We work with the world&rsquo;s leading model labs to push the frontier of agent capabilities. Polymath is backed by Base10, Founders Future, Y Combinator, and other incredible investors &amp; angels. We've raised an $8M seed, and are growing out our founding team.
About the role
We&rsquo;re hiring a Member of Technical Staff - Engineering to build the infrastructure and systems that power our environment simulation products. You&rsquo;ll work on the technical foundation that makes it possible to train and evaluate autonomous agents in complex, realistic environments. You&rsquo;ll be a member of the founding team and should expect to wear multiple hats. While this role is engineering-leaning, we&rsquo;re looking for people who are energized by hard technical problems and excited to operate at the intersection between engineering and research. Examples of projects you could work on include:<ul><li>
Developing an advanced environment simulation engine for training &amp; evaluating autonomous AI agents</li><li>
Building scalable infrastructure to run thousands of simulation environments in parallel</li><li>
Optimizing the performance of complex, stateful simulation environments</li><li>
Tooling to collect data at scale, and improve environment and task creation processes</li><li>
Publishing research</li></ul>
You&rsquo;ll be a good fit if you:<ul><li>
Have strong engineering fundamentals and are a prolific user of AI tools</li><li>
Have experience with infrastructure, containerization, and networking</li><li>
Have experience with large scale distributed systems and data systems</li></ul>
Perks:<ul><li>
Comprehensive health, dental, and vision insurance</li><li>
401(k)</li><li>
Unlimited PTO</li><li>
Free meals with the team</li><li>
Wellness stipend &amp; learning stipend</li><li>
Top of the line tech</li><li>
Frequent team activities and outings</li></ul>
Culture:<ul><li>
Polymath is a team of researchers, engineers, and operators focused on advancing the frontier of safe, superintelligent AI agents.</li><li>
We have a flat organizational structure. We believe that people do their best work when they&rsquo;re self-motivated and driven by a desire to learn, contribute to the team&rsquo;s goals, and advance scientific progress.</li><li>
We&rsquo;re looking for folks who ship fast, set high standards for themselves, and are great team players. You&rsquo;ll be a member of our founding team: have fun, learn a lot, and do high-impact work alongside great people.</li></ul>
Compensation Range: $150K - $300K</div>

Member of Technical Staff - Engineering

OpenAI

About the team
 
The Finance Data team is embedded within the CFO Org and is responsible for building internal data products that scale analytics across business teams and drive efficiencies in our daily operations. This team provides technical guidance on high-impact, scalable projects across Finance, and is the subject-matter expert in financial and transactional data that supports our Finance day-to-day operations.
 
About the Role
 
The Finance Data team is embedded within the OpenAI CFO Org (not under Engineering nor Product) and our team's mandate is ambitious yet simple:
 
1) The CFO Org has the data required to be Public Company Ready.
 
2) The CFO Org has all the data it needs to execute swiftly on our AI first roadmap.
 
3) Controllership is able to close the books without any manual spreadsheets in the shortest timeframe and with zero material risks.
 
As an Data Engineer on the Finance Data team, you will be setting the foundation to scale analytics across our business functions and impart best data practices for a rapidly growing organization. We aspire to build the Finance team of the future.
 
In addition, you will work collaboratively with key stakeholders in Finance and other business teams to understand their pain points and take the lead in proposing viable, future-proof solutions to resolve them. You will also autonomously lead your own projects that deliver business impact and help cultivate a mature data culture among Finance teams.
 
We are looking for a seasoned Data Engineer who has a proven track record of owning the entire data stack at high transaction volume companies, managing business critical ETL pipelines consumed by non-technical teams. In this role you will serve the Head of Supply Chain Systems and be responsible for leading our manufacturing, OTC data mart strategy. The goal is to enable end-to-end asset and inventory traceability for our supply chain infrastructure by end of year 2026. We actually need someone who excels in dynamic environments, adapts quickly to changing needs, and confidently navigates ambiguous or evolving requirements. If you're energized by solving technical problems without a playbook and comfortable wearing multiple hats, this role is for you! To clarify, you will not be responsible for training ML models and neither would we describe this role as ‘product analytics’.
 
You might thrive in this role if you: 
Have 3+ years of experience as a data engineer and 8+ years of any software engineering experience(including data engineering).
 
Proficiency in at least one programming language commonly used within Data Engineering, such as Python, Scala, or Java.
 
Experience with distributed processing technologies and frameworks, such as Hadoop, Flink and distributed storage systems (e.g., HDFS, S3).
 
Expertise with any of ETL schedulers such as Airflow, Dagster, Prefect or similar frameworks.
 
Solid understanding of Spark and ability to write, debug and optimize Spark code.
 
This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees.
 
About OpenAI
 
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
 
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
 
For additional information, please see
 
OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement
 
.
 
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
 
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through
 
this form
 
. No response will be provided to inquiries unrelated to job posting compliance.
 
We are committed to providing reasonable accommodations to applicants with disabilities.
 
OpenAI Global Applicant Privacy Policy
 
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
 
Compensation
 
$293K – $325K + Offers Equity

Data Engineer, Finance

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