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advisor - scientific data engineer Jobs in San Francisco

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advisor scientific data engineer

Eli Lilly

<div><p>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.</p><p></p><h1 class="jobSectionHeader"><b>
The Opportunity</b></h1><p></p><p>
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.</p><p>
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.</p><p></p><p>
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.</p><h1 class="jobSectionHeader"><b>
Responsibilities</b></h1><p></p><h2 class="jobSectionHeader"><b>
Data Harmonization and Lakehouse Architecture</b></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"><b>
Semantic Layer and Schema Engineering</b></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"><b>
AI-Ready Data Products</b></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"><b>
Qualifications</b></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"><b>
Additional Skills/Preferences</b></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><p></p><p>
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.</p><p></p><p>
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.</p><p><br>
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.</p><p></p><p>
Actual compensation will depend on a candidate&rsquo;s education, experience, skills, and geographic location. The anticipated wage for this position is</p>
$166,500 - $266,200<p></p><p>
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.</p><p></p><p>
#WeAreLilly</p></div>

Advisor - Scientific Data Engineer

Lila Sciences

<div><p><b>Your Impact at LILA</b></p>
<p>
Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Science AI (LSAI), ML engineers build and operate the systems that turn generative models and reasoning frameworks into production capabilities powering automated scientific discovery across Lila's life science domains.</p>
<p>
We are seeking a Principal ML Engineer to design, build, and scale the ML infrastructure behind models spanning biological sequence design, molecular structure prediction, antibody engineering, and multimodal scientific reasoning. You will own critical systems end to end, from training pipelines and distributed compute to model deployment and integration into Lila's closed-loop discovery engine.</p>
<p>
This is a high-impact IC role for someone who operates at the intersection of ML systems engineering and life science applications. You will shape the technical direction for how ML models are trained, evaluated, and deployed at scale, collaborate closely with AI scientists and experimental researchers to close the computational-experimental loop, and drive Lila's ML infrastructure toward the next generation of capabilities.</p>
<p><b>
What You'll Be Building</b></p>
<ul>
<li>Design, build, and optimize large-scale training pipelines for generative models on biological and chemical data, including distributed training across GPU clusters</li>
<li>Own production ML systems end to end: model deployment, serving infrastructure, monitoring, and reliability for models used in Lila's scientific workflows</li>
<li>Architect ML infrastructure that supports rapid iteration across sequence design, structure prediction, and multimodal scientific reasoning workloads</li>
<li>Drive the engineering side of Lila's &quot;Lab-in-the-Loop&quot; lifecycle: build pipeline models, integrate experimental feedback loops, and ensure model outputs are actionable for downstream scientific workflows</li>
<li>Define and advance ML engineering standards, tooling, and best practices across the AI organization</li>
<li>Collaborate with AI scientists to translate research prototypes into robust, scalable production systems, bridging the research-to-deployment gap</li>
</ul>
<p><b>What You'll Need to Succeed</b></p>
<ul>
<li>Master's degree or higher in Computer Science, Machine Learning, or a related quantitative field (or Bachelor's with equivalent professional experience)</li>
<li>10+ years of hands-on experience building and operating production ML systems at scale</li>
<li>Deep expertise in distributed training infrastructure, including experience with large-scale GPU clusters (AWS, GCP, or on-prem)</li>
<li>Strong software engineering fundamentals: system design, production-grade code, CI/CD, observability, and reliability practices</li>
<li>Proficiency in ML frameworks (PyTorch, JAX, or TensorFlow) with experience optimizing training and inference performance</li>
<li>Demonstrated ability to drive technical direction for ML infrastructure independently, from architecture through implementation</li>
<li>Track record of cross-functional collaboration with research scientists, translating between ML methodology and engineering execution</li>
</ul>
<p><b>Bonus Points For</b></p>
<ul>
<li>Experience building training or inference infrastructure for generative models applied to biological sequences, molecular structures, or scientific data</li>
<li>Experience with agentic frameworks, active learning loops, or closed-loop experimental workflows</li>
<li>Contributions to open-source ML tools, frameworks, or infrastructure projects</li>
<li>Familiarity with at least one life science domain (molecular biology, genomics, protein engineering, or nucleic acid design)</li>
<li>Experience with model evaluation frameworks for scientific applications where ground truth is sparse or delayed</li></ul><p></p><div><p><b><br>
About LILA</b></p>
<p>
Lila Sciences is building Scientific Superintelligence&trade; to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.</p>
<p>
LILA combines advanced AI models with proprietary AI Science Factory&trade; instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.</p>
<p>
Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.</p>
<p><b>
We're All In</b></p>
<p>
Lila Sciences is 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.</p>
<p>
Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.</p>
<p><b>
A Note to Agencies</b></p>
<p><i>
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.</i></p></div></div>

Principal, Machine Learning Engineer

Capital One

<div>Distinguished Data Engineer - Card Data<p></p><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p>
Distinguished Data Engineers are individual contributors who strive to be diverse in thought so we visualize the problem space. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. Distinguished Engineers will significantly impact our trajectory and devise clear roadmaps to deliver next generation technology solutions.</p><p><b><br>
About the Team: </b>Capital One is seeking a Distinguished Data Engineer, to work in our Credit Card Technology Data Engineering Team and build the future of financial services. We are a fast-paced, mission-driven group responsible for managing and leveraging petabytes of sensitive, real-time and batch data that powers everything from fraud detection models and personalized reward systems to regulatory compliance reporting. As a leader in Data Engineering, you won't just move data; you'll architect high-availability that directly influence millions of customer experiences and secure billions in transactions daily. You'll own critical data domains end-to-end, working cross-functionally with ML Scientists, Product Managers, and Business Analysts teams etc to solve complex, high-stakes problems with cutting-edge cloud technologies (like Snowflake, Kafka, and AWS). If you thrive on technical challenges, demand data integrity, and want your work to have a clear, measurable impact on the bank&rsquo;s core profitability and security, this is your team.</p><p><br>
This leader must have the ability to attract and recruit the industry&rsquo;s best talent, and simultaneously have the technical chops to ensure that we build compelling, customer-oriented solutions in an iterative methodology. Success in the role requires an innovative mind, a proven track record of delivering next generation software and data products, rigorous analytical skills, and a passion for delivering customer value through automation, machine learning and predictive analytics.</p><p><b><br>
Our Distinguished Engineers Are:</b></p><ul><li><p><br>
Deep technical experts and thought leaders that help accelerate adoption of the very best engineering practices, while maintaining knowledge on industry innovations, trends and practices</p></li><li><p>
Visionaries, collaborating on Capital One&rsquo;s toughest issues, to deliver on business needs that directly impact the lives of our customers and associates</p></li><li><p>
Role models and mentors, helping to coach and strengthen the technical expertise and know-how of our engineering and product community</p></li><li><p>
Evangelists, both internally and externally, helping to elevate the Distinguished Engineering community and establish themselves as a go-to resource on given technologies and technology-enabled capabilities</p></li></ul><p><b><br>
Responsibilities:</b></p><ul><li><p>
Build awareness, increase knowledge and drive adoption of modern technologies, sharing consumer and engineering benefits to gain buy-in</p></li><li><p>
Strike the right balance between lending expertise and providing an inclusive environment where others&rsquo; ideas can be heard and championed; leverage expertise to grow skills in the broader Capital One team</p></li><li><p>
Promote a culture of engineering excellence, using opportunities to reuse and innersource solutions where possible</p></li><li><p>
Effectively communicate with and influence key stakeholders across the enterprise, at all levels of the organization</p></li><li><p>
Operate as a trusted advisor for a specific technology, platform or capability domain, helping to shape use cases and implementation in an unified manner</p></li><li><p>
Lead the way in creating next-generation talent for Tech, mentoring internal talent and actively recruiting external talent to bolster Capital One&rsquo;s Tech talent</p></li></ul><p><b><br>
Basic Qualifications:</b></p><ul><li><p>
Bachelor&rsquo;s Degree</p></li><li><p>
At least 7 years of experience in data engineering</p></li><li><p>
At least 3 years of experience in data architecture</p></li><li><p>
At least 2 years of experience building applications in AWS</p></li></ul><p><b><br>
Preferred Qualifications:</b></p><ul><li><p>
Masters&rsquo; Degree</p></li><li><p>
9+ years of experience in data engineering</p></li><li><p>
3+ years of data modeling experience</p></li><li><p>
2+ years of experience with ontology standards for defining a domain</p></li><li><p>
2+ years of experience using Python, SQL or Scala</p></li><li><p>
1+ year of experience deploying machine learning models</p></li><li><p>
3+ years of experience implementing big data processing solutions on AWS</p></li></ul><p><b><i><br>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position</i></b></p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><p></p><p>
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.</p><p></p>
Chicago, IL: $244,700 - $279,200 for Distinguished Data Engineer<br>
<p></p>
McLean, VA: $269,100 - $307,200 for Distinguished Data Engineer<br>
<p></p>
New York, NY: $293,600 - $335,100 for Distinguished Data Engineer<br>
<p></p>
Richmond, VA: $244,700 - $279,200 for Distinguished Data Engineer<br>
<p></p>
San Francisco, CA: $293,600 - $335,100 for Distinguished Data Engineer<p></p><p><br>
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.</p><p></p>
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.<p></p><p>
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.</p><p></p>
This role is expected to accept applications for a minimum of 5 business days.<p></p>
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.<p></p><p>
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.</p><p></p><p>
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com</p><p></p><p>
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.</p><p></p><p>
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</p></div>

Distinguished Data Engineer - Card Data

Biohub

<div><div><p>Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere.</p></div><h2 class="jobSectionHeader"><b>
The Team</b></h2>
<p>
Biohub is leading the new era of AI-powered biology to cure or prevent disease through its 501c3 medical research organization, with the support of the Chan Zuckerberg Initiative.</p>
<p>
Within Biohub, Bioengineering is a team of engineers with a diverse set of skills, including electronics, optics, imaging, automation, mechatronics, fluidics, software development, etc. We design and build custom instrumentation and automation systems to support the Biohub's scientific mission.</p>
<h2 class="jobSectionHeader"><b>
The Opportunity</b></h2>
<p>
We are seeking an experienced Lab Automation Applications Engineer to design, develop, and maintain automated protocols that support cell biology research programs. This role is ideal for an automation professional who can independently lead protocol development projects, optimize workflows, and serve as a technical resource for researchers. You will work closely with research scientists, hardware and software engineers, data scientists, laboratory staff, and facility managers to develop automation protocols that enhance throughput, reproducibility, and data quality. In this role, you will take ownership of end-to-end automation protocols, from initial method development through validation, production deployment, quality control and performance monitoring. You will also help drive continuous improvement of our automation capabilities.</p>
<h2 class="jobSectionHeader"><b>
What You'll Do</b></h2>
<ul><li>Lead the design, development, testing, and validation of automated protocols for cell biology (including multi-day cell culture and passaging), cell imaging, and molecular biology.</li>
<li>Independently program and optimize methods on Hamilton STAR/Vantage platforms using VENUS software, and other platforms, such as Opentrons and Agilent Bravos.</li>
<li>Partner with research scientists and technology teams to scope automation protocols, define requirements, and deliver solutions that meet scientific and throughput goals.</li>
<li>Develop and maintain robust quality control processes for automated workflows, including run validation, error handling, and performance monitoring.</li>
<li>Create and maintain comprehensive documentation including method specifications, SOPs, validation reports, and training materials.</li>
<li>Troubleshoot and resolve, in collaboration with hardware and software engineers and/or scientists, complex hardware, software, and method issues.</li>
<li>Manage vendor relationships for maintenance and support.</li>
<li>Mentor junior automation engineers and contribute to the team's technical growth and best practices.</li>
<li>Identify and implement process improvements that increase throughput, reliability, and data quality across the automation platform.</li>
</ul><h2 class="jobSectionHeader"><b>What You'll Bring</b></h2>
<p><b>
Essential</b></p>
<ul>
<li>Bachelor's degree in Engineering, Biology, Biochemistry, or related field.</li>
<li>5+ years of hands-on experience with laboratory automation in a biology research or industrial biotech environment.</li>
<li>Demonstrated expertise programming and running automated liquid handling systems. Experience with Hamilton STAR and Vantage liquid handlers and the VENUS software are a big plus.</li>
<li>Experience with robotic arms, robot programming, PLC systems, or motion control</li>
<li>Experience integrating liquid handlers with peripheral lab instruments and scheduling systems.</li>
<li>Proficiency in Python or another scripting language for automation support, data analysis, or custom tooling.</li>
<li>Strong understanding of molecular biology, biochemistry, and cell biology laboratory techniques.</li>
<li>Demonstrated ability to independently manage projects from concept through deployment.</li>
<li>Demonstrated experience with proper documentation of protocols and operating procedures, performance/quality control metrics, etc.</li>
<li>Commitment to reproducible research practices and rigorous documentation</li>
<li>Demonstrated ability to think creatively and work independently.</li>
<li>Excellent problem-solving skills and the ability to quickly adapt to new technological challenges and troubleshoot complex technical problems.</li>
<li>Eager to learn new methods, protocols and technologies.</li>
<li>Strong communication and interpersonal skills.</li>
<li>Highly collaborative spirit and strong teamwork skills.</li>
</ul>
<p><b>Nice to Have</b></p>
<ul>
<li>Experience with live cell imaging</li>
<li>Experience with laboratory data management systems (e.g., LIMS, ELN)</li>
<li>Knowledge of data analysis, statistical methods, and workflow management software</li>
</ul><h2 class="jobSectionHeader"><b>Compensation</b></h2>
<p>
The San Francisco, CA base pay range for a new hire in this role is $190,000.00 - $261,800.00. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.</p>
<p>
This position may be eligible to participate in Biohub's discretionary annual performance bonus program. Bonus eligibility and targets are determined in accordance with Biohub's total rewards philosophy and may vary by role.</p>
<h2 class="jobSectionHeader"><b>
Better Together</b></h2>
<p>
As we grow, we're excited to strengthen in-person connections and cultivate a collaborative, team-oriented environment. This role is a hybrid position requiring you to be onsite for at least 60% of the working month, approximately 3 days a week, with specific in-office days determined by the team's manager. The exact schedule will be at the hiring manager's discretion and communicated during the interview process.</p>
<h2 class="jobSectionHeader"><b>
Benefits for the Whole You</b></h2>
<p>
We're thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible.</p>
<ul>
<li>Provides a generous employer match on employee 401(k) contributions to support planning for the future.</li>
<li>Paid time off to volunteer at an organization of your choice.</li>
<li>Funding for select family-forming benefits.</li>
<li>Relocation support for employees who need assistance moving</li>
</ul>
<p>If you're interested in a role but your previous experience doesn't perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.</p>
<p>
#LI-Hybrid</p></div>

Senior R&D Engineer, Lab Automation Applications Engineer

Prolific

<div>
 AI Trainer - Neuroscience Specialist (Remote Advisory)
 <br/>
 <br/>
 <strong>
  About Prolific
  <br/>
  <br/>
 </strong>
 Prolific is not just another player in the AI space &ndash; we are building the biggest pool of quality human data in the world.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 <em>
  The role
  <br/>
  <br/>
 </em>
 We are seeking
 <strong>
  Neuroscience Experts
 </strong>
 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.
 <br/>
 <br/>
 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
 <strong>
  $40+/h
 </strong>
 where your technical expertise directly influences how AI understands and summarizes complex research.
 <br/>
 <br/>
 <em>
  What you'll bring
  <br/>
  <br/>
 </em>
 <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.
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  What you'll be doing in the role
  <br/>
  <br/>
 </em>
 <ul>
  <li>
   <strong>
    Scientific Review:
   </strong>
   review scientific papers alongside LLM-generated graphical abstracts.
  </li>
  <li>
   <strong>
    Fact-Checking:
   </strong>
   identify issues and inaccuracies where the graphical abstract does not faithfully represent the source scientific paper.
  </li>
  <li>
   <strong>
    Expert Verification:
   </strong>
   use your domain knowledge to ensure that technical concepts are visually and textually summarized correctly.
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  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
  <br/>
  <br/>
 </em>
 <em>
  Why Prolific is a great platform to join as a Participant
  <br/>
  <br/>
 </em>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 <em>
  Links to more information on Prolific
  <br/>
  <br/>
 </em>
 Website
 <br/>
 <br/>
 Youtube
 <br/>
 <br/>
 <em>
  Privacy Statement
  <br/>
  <br/>
 </em>
 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)

Prolific Academic Ltd

<div><h2 class="jobSectionHeader"><b>Computer Sciences - Graduates - AI Training</b></h2>
<h4 class="jobSectionHeader"><b><i>About Prolific</i></b></h4>
<p>
Prolific is not just another player in the AI space &ndash; we are building the biggest pool of quality human data in the world.</p>
<p>
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.</p>
<h4 class="jobSectionHeader"><b><i>
The role</i></b></h4>
<p>
We're looking for <b>Computer Science Specialists</b> to join our Expert Network to help train and evaluate cutting-edge AI models. If you have a background in CS research or technical analysis, we'll send you a quick 10- to 15-minute test to assess your skills. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to help AI understand and summarize complex scientific data.</p>
<p>
Researchers looking for your skills tend to pay up to <b>$60/hr, depending on skills and experience level</b>. You must be prepared to complete paid tasks that <b>require one hour of uninterrupted work</b>, though many are shorter.</p>
<h4 class="jobSectionHeader"><b><i>
What you'll bring</i></b></h4>
<ul><li><b>Educational Background:</b> at minimum, a <b>BSc (Bachelor of Science) in Computer Science</b> or a closely related technical field.</li>
<li><b>Technical Literacy:</b> ability to interpret research papers, understand complex algorithms, and review code logic.</li>
<li><b>Analytical Mindset:</b> high level of cognitive competency with a sharp eye for technical hallucinations or logical flaws.</li>
<li><b>Professional Verification:</b> a valid LinkedIn profile to verify your degree and background during the screening process.</li>
<li><b>A PayPal account to receive payment from our clients</b></li>
</ul><h4 class="jobSectionHeader"><b><i>What you'll be doing in the role</i></b></h4>
<ul><li><b>AI Evaluation &amp; Ranking:</b> comparing multiple AI-generated responses to technical prompts and ranking them based on accuracy, logic, and safety.</li>
<li><b>Scientific Review:</b> reviewing CS research papers alongside AI-generated summaries and graphical abstracts to ensure scientific integrity.</li>
<li><b>Fact-Checking:</b> identifying inaccuracies where the AI has misinterpreted technical data, formulas, or research findings.</li>
<li><b>RLHF (Reinforcement Learning from Human Feedback):</b> providing the human &quot;ground truth&quot; to help models align with professional standards in software engineering and data science.</li>
<li><b>Code &amp; Logic Verification:</b> auditing AI-generated code snippets or architectural diagrams for structural and functional correctness.</li>
</ul><h4 class="jobSectionHeader"><b><i>Key Technologies</i></b></h4>
<ul><li><b>Generative AI &amp; LLMs:</b> training the next generation of technical and reasoning models.</li>
<li><b>Technical Documentation:</b> working with research papers, code repositories, and data visualizations.</li>
<li><b>Verification Frameworks:</b> using structured evaluation rubrics to audit AI performance.</li>
</ul><h4 class="jobSectionHeader"><b><i>Why Prolific is a great platform to join as a Participant</i></b></h4>
<p>
Joining our Expert Network 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.</p>
<p>
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.</p>
<div>
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.</div>
<h4 class="jobSectionHeader"><b><i>Links to more information on Prolific</i></b></h4>
<p>
Website</p>
<p>
Youtube</p>
<h4 class="jobSectionHeader"><b><i>
Privacy Statement</i></b></h4>
<p>
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.</p></div><p></p>

Computer Sciences - Graduates - AI Training - San Francisco, US

<div>
 <strong>
  AI Trainer &ndash; Research Scientists
  <br/>
  <br/>
 </strong>
 <em>
  <strong>
   About Prolific
   <br/>
   <br/>
  </strong>
 </em>
 Prolific is not just another player in the AI space &ndash; we are building the biggest pool of quality human data in the world.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 <em>
  <strong>
   The role
   <br/>
   <br/>
  </strong>
 </em>
 We&rsquo;re looking for people with Research Scientist experience to work as self-employed AI Trainers to help train and evaluate cutting-edge AI models from some of the world&rsquo;s biggest AI labs. If you have the necessary experience, we&rsquo;ll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you&rsquo;ll be invited to join Prolific as a Domain Expert participant, where you&rsquo;ll get paid to train and evaluate powerful AI models.
 <br/>
 <br/>
 Researchers looking for your skills tend to pay up to $50/hr subject to the length of tasks available. If successful, you must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter.
 <br/>
 <br/>
 <em>
  <strong>
   What you&rsquo;ll be doing in the role
   <br/>
   <br/>
  </strong>
 </em>
 Completing AI training tasks such as analyzing, editing, and writing research-focused content
 <br/>
 <br/>
 Judging the performance of AI on research design, methodology, and scientific reasoning prompts
 <br/>
 <br/>
 Improving cutting-edge AI models using your experience in research and experimentation
 <br/>
 <br/>
 <em>
  <strong>
   What you&rsquo;ll bring
   <br/>
   <br/>
  </strong>
 </em>
 Experience working as a Research Scientist or in a closely related research role
 <br/>
 <br/>
 A strong understanding of scientific methodology, experimental design, and data analysis
 <br/>
 <br/>
 A willingness to take our skills verification test to assess your suitability for our Domain Expert participant pool
 <br/>
 <br/>
 Strong attention to detail and the ability to concentrate on complex tasks for up to one hour at a time
 <br/>
 <br/>
 A reliable and fast internet connection and access to a computer
 <br/>
 <br/>
 A Paypal account to receive payment from our clients*
 <br/>
 <br/>
 <em>
  <strong>
   Why Prolific is a great platform to join as a Domain Expert participant
   <br/>
   <br/>
  </strong>
 </em>
 Joining our platform as a Prolific participant will give you the chance to influence the AI models of the future. 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 <ul>
  <li>
   Participants are self-employed and need to declare earnings to their respective tax authorities. Prolific has no liability for any tax obligations or reporting requirements resulting from compensation received through this platform. Each participant is solely responsible for compliance with applicable tax laws in their jurisdiction.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Links to more information on Prolific
  <br/>
  <br/>
 </strong>
 Website
 <br/>
 <br/>
 Youtube
 <br/>
 <br/>
 Privacy Statement
 <br/>
 <br/>
 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 information.
</div>


AI Training - Research Scientist (PST)

Explore 357+ Advisor scientific data engineer in San Francisco this May. Find roles across top companies and apply now to boost your career.