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ai research engineer, fair chemistry Jobs in San Francisco

ai research engineer, fair chemistry

ai scientist - llms [32814] Jobs in San Francisco

ai scientist - llms [32814]

ai/machine learning engineer intern Jobs in San Francisco

ai/machine learning engineer intern

ai scientist llms 32814

Stealth AI Startup

<div>
 
 About the Role
 
 
 We are seeking an exceptional Lead Researcher to lead and scale a world-class AI research organization focused on advancing the state of the art in machine learning, large language models, and applied AI systems. This role is both
 
 strategic and hands-on
 
 , responsible for defining long-term research vision while actively contributing to breakthrough innovations that directly impact product and business outcomes.
 
 
 As Head of Research, you will build, mentor, and manage a high-caliber team of researchers and research engineers, partner closely with executive leadership, and translate cutting-edge research into scalable, real-world systems.
 
 
 Key Responsibilities
 
 <ul>
 <li>
 Define and own the
 
 research vision and roadmap
 
 , aligned with company strategy and long-term goals
 </li>
 <li>
 Lead and grow a team of
 
 AI Researchers, Applied Scientists, and Research Engineers
 
 </li>
 <li>
 Drive innovation across areas such as:
 </li>
 <li>
 Large Language Models (LLMs)
 </li>
 <li>
 Reasoning and planning systems
 </li>
 <li>
 Representation learning
 </li>
 <li>
 Robustness, safety, and evaluation
 </li>
 <li>
 Multimodal and agent-based systems
 </li>
 <li>
 Balance
 
 long-horizon exploratory research
 
 with
 
 near-term applied research
 
 that powers products
 </li>
 <li>
 Ensure research excellence through strong scientific rigor, reproducibility, and evaluation standards
 </li>
 <li>
 Collaborate with Product, Engineering, and Leadership to transition research into production
 </li>
 <li>
 Represent the company externally through publications, conferences, and industry engagement
 </li>
 <li>
 Establish best practices for research processes, tooling, and infrastructure
 </li>
 <li>
 Mentor senior researchers and develop future research leaders
 </li>
 </ul>
 
 Required Qualifications
 
 <ul>
 <li>
 PhD in Computer Science, Machine Learning, AI, or a closely related field (or equivalent research experience)
 </li>
 <li>
 0-7 years of experience in AI/ML research, with at least several years in a
 
 research role
 
 </li>
 <li>
 Proven track record of
 
 high-impact research contributions
 
 (top-tier conferences, journals, or widely adopted systems)
 </li>
 <li>
 Deep expertise in modern ML techniques, especially
 
 LLMs, deep learning, and foundation models
 
 </li>
 <li>
 Experience leading and scaling research teams in industry or advanced research labs
 </li>
 <li>
 Strong understanding of the tradeoffs between research innovation and production constraints
 </li>
 <li>
 Ability to communicate complex technical ideas clearly to both technical and non-technical stakeholders
 </li>
 </ul>
 
 Preferred Qualifications
 
 <ul>
 <li>
 Experience leading research at a top AI lab, FAANG company, or well-known AI startup
 </li>
 <li>
 Publications at leading venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP)
 </li>
 <li>
 Experience with model training at scale, including distributed systems and ML infrastructure
 </li>
 <li>
 Background in deploying research models into real-world products
 </li>
 <li>
 Prior experience influencing company-level technical strategy
 </li>
 </ul>
 
 What We Offer
 
 <ul>
 <li>
 
 Base salary up to $500,000
 
 , plus competitive equity
 </li>
 <li>
 Opportunity to shape the future direction of cutting-edge AI research
 </li>
 <li>
 Access to significant compute and research resources
 </li>
 <li>
 Collaboration with elite engineers, researchers, and product leaders
 </li>
 <li>
 A culture that values deep thinking, experimentation, and long-term impact
 </li>
 </ul>
 
 
</div>

AI Scientist - LLMs [32814]

Asana

<div>
 We're looking for a Staff Data Scientist to help define Asana's growth strategy as users increasingly discover and adopt software through LLM interfaces like ChatGPT, Claude, and Gemini. With millions of knowledge workers now starting their workday in conversational AI tools, we're at an inflection point in how productivity software reaches users. You'll drive Asana's acquisition playbook for the emerging LLM-driven channels and re-imagine new customer onboarding in the AI-era. As part of the PLG organization, you'll leverage data to influence how new users discover, learn about, and decide to start using and paying for Asana.
 
 
 Asana's Data Science team helps us fulfill our mission by informing strategy, defining success metrics, and identifying new ways to deliver user value. Data scientists are at the crux of deepening our understanding of the customers and driving more business outcomes by leveraging experimentation, causal inference, statistical and machine learning techniques, and data storytelling.
 
 
 This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.
 
 
 
 What you&rsquo;ll achieve:
 
 
 
 <ul>
 <li>
 Work closely with Product Managers and User Researchers (UXR) to understand the needs of our new customers in their first few minutes of interaction with Asana, employing data frameworks and methodologies to understand our user segments, visualize the new user funnel, identify levers for driving conversion revenue, and personalize the onboarding journey to ensure better adoption outcomes.
 </li>
 <li>
 Act as the "Data Lead" in a triad with Product and Engineering stakeholders to identify multi-year growth opportunities and prioritize the roadmap.
 </li>
 <li>
 Design experiments that measure product progress, and own key performance metrics.
 </li>
 <li>
 Collaborate and mentor fellow Data Scientists in the team to research, identify and disseminate best practices across teams.
 </li>
 <li>
 Work in a high-performance, dynamic team with a strong focus on velocity and software quality and learn about the upcoming field of AI-Optimization and how LLMs can help boost Asana&rsquo;s value proposition.
 
 
 </li>
 </ul>
 
 About you:
 
 
 
 <ul>
 <li>
 5-7 years of data science experience, with majority in growth-focused roles at B2B SaaS companies
 </li>
 <li>
 Proven track record driving acquisition and activation for B2B SaaS products, with specific experience in top-of-funnel growth and new user acquisition.
 </li>
 <li>
 0&rarr;1 builder mentality. You've demonstrated the ability to thrive in highly ambiguous environments where you're inventing new playbooks rather than executing existing ones. You're energized by pioneering work.
 </li>
 <li>
 Experience with AI/ML products, LLM APIs, or third-party platform integrations. Strong preference for candidates who've worked with conversational AI or built features integrating ChatGPT, Claude, or similar platforms.
 </li>
 <li>
 Strong analytical foundation with deep fluency in experimentation, A/B testing, and funnel optimization.
 </li>
 <li>
 Exceptional cross-functional leadership. You write crisply, tell clear stories, and can influence across product, engineering, design, partnerships, sales, and executive stakeholders. You bring clarity to ambiguity.
 </li>
 <li>
 Strategic business acumen to balance user experience with revenue objectives while translating emerging technology trends into actionable product strategy.
 </li>
 <li>
 Genuine AI enthusiasm. You're curious, adaptable, and genuinely excited about how LLMs are transforming software discovery and adoption.
 </li>
 <li>
 Expert in relational data modeling and SQL and fluent in at least one modern language useful for data processing (e.g. R, Python, or Scala).
 </li>
 <li>
 Familiarity with statistical methods including experimental design, regression, causal inference with observational data and time series modeling.
 </li>
 <li>
 Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.
 
 
 </li>
 </ul>
 At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply.
 
 
 
 What We&rsquo;ll Offer
 
 
 
 Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.
 
 
 For this role, the estimated base salary range is between $248,000&ndash;282,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.
 
 
 In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.
 
 
 We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:
 
 
 <ul>
 <li>
 Mental health, wellness &amp; fitness benefits
 </li>
 <li>
 Career coaching &amp; support
 </li>
 <li>
 Inclusive family building benefits
 </li>
 <li>
 Long-term savings or retirement plans
 </li>
 <li>
 In-office culinary options to cater to your dietary preferences
 
 
 </li>
 </ul>
 These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.
 
 
 
 About Us
 
 
 
 Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong.
 
 
 
 Join Asana&rsquo;s Talent Network
 
 to stay up to date on job opportunities and life at Asana.
 
 
</div>

Data Scientist

Superhuman

<div>
 
 Superhuman offers a dynamic hybrid working model for this role. This flexible approach gives team members the best of both worlds: plenty of focus time along with in-person collaboration that helps foster trust, innovation, and a strong team culture.
 
 
 
 
 About Superhuman
 
 
 
 Grammarly is now part of Superhuman, the AI productivity platform on a mission to unlock the superhuman potential in everyone. The Superhuman suite of apps and agents brings AI wherever people work, integrating with over 1 million applications and websites. The company&rsquo;s products include Grammarly&rsquo;s writing assistance, Coda&rsquo;s collaborative workspaces, Mail&rsquo;s inbox management, and Go, the proactive AI assistant that understands context and delivers help automatically. Founded in 2009, Superhuman empowers over 40 million people, 50,000 organizations, and 3,000 educational institutions worldwide to eliminate busywork and focus on what matters.
 
 Learn more at superhuman.com and about our values here.
 
 
 
 
 The Opportunites
 
 
 
 We are building a platform for AI Agents to come together and solve arbitrarily complex tasks, leveraging Superhuman ubiquitous UI. As a Machine Learning Engineer on this team, you will be at the heart of our company's transformation.
 
 
 <ul>
 <li>
 Shape the Future of Productivity: Play a pivotal role in evolving Grammarly from a beloved writing assistant into an indispensable, AI-native productivity suite for enterprises.
 </li>
 <li>
 Build a Groundbreaking AI Agent Platform: Spearhead the development of a new platform where multiple AI agents collaborate to solve complex user problems. You will be responsible for the core orchestration, routing, and planning systems.
 </li>
 <li>
 Own Critical ML Systems: Develop and deploy sophisticated ML models for core product experiences, including search ranking and proactive suggestions that anticipate user needs.
 </li>
 <li>
 Integrate Cutting-Edge AI: Work at the forefront of the AI landscape, building ML components that integrate with the latest and most powerful models to create magical user experiences.
 </li>
 <li>
 Thrive in a High-Impact Environment: Join a foundational team where you will operate with a high degree of autonomy and product sense in a fast-paced, ambiguous environment.
 </li>
 <li>
 Ship Your Work Fast: Move quickly from idea to impact. We have no red tape or endless approvals&mdash;just a focus on making meaningful contributions to a platform used by millions.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 MS / PhD in Computer Science.
 </li>
 <li>
 5+ years of industry experience as a machine learning engineer or applied research scientist.
 </li>
 <li>
 A deep understanding of modern algorithms and approaches to ML, NLP, and LLMs.
 </li>
 <li>
 Experience building LLM-based products.
 </li>
 <li>
 A deep care about the end-user experience and strives to ensure high quality.
 </li>
 <li>
 Has a demonstrated ability to work independently with minimal guidance, proactively manages tasks and priorities across multiple projects, analyzes and executes work efficiently, collaborates effectively with cross-functional teams, and thrives in fast-paced, results-driven environments.
 
 
 </li>
 </ul>
 We invite you to share your knowledge, experience, and goals with us to help us find the best team match for you. Tell us your superpower!
 
 
 
 Compensation And Benefits
 
 
 
 Superhuman offers all team members competitive pay along with a benefits package encompassing the following and more:
 
 
 <ul>
 <li>
 Excellent health care (including a wide range of medical, dental, vision, mental health, and fertility benefits)
 </li>
 <li>
 Disability and life insurance options
 </li>
 <li>
 401(k) and RRSP matching
 </li>
 <li>
 Paid parental leave
 </li>
 <li>
 20 days of paid time off per year, 12 days of paid holidays per year, two floating holidays per year, and flexible sick time
 </li>
 <li>
 Generous stipends (including those for caregiving, pet care, wellness, your home office, and more)
 </li>
 <li>
 Annual professional development budget and opportunities
 
 
 </li>
 </ul>
 Superhuman takes a market-based approach to compensation, which means base pay may vary depending on your location. Our US locations are categorized into two compensation zones based on proximity to our hub locations.
 
 
 Base pay may vary considerably depending on job-related knowledge, skills, and experience. The expected salary ranges for this position are outlined below by compensation zone and may be modified in the future.
 
 
 United States
 
 
 Zone 1: $250,000 - $385,000/year (USD)
 
 
 
 We encourage you to apply
 
 
 
 At Superhuman, we value our differences, and we encourage all to apply&mdash;especially those whose identities are traditionally underrepresented in tech organizations. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, ancestry, national origin, citizenship, age, marital status, veteran status, disability status, political belief, or any other characteristic protected by law. Superhuman is an equal opportunity employer and a participant in the US federal E-Verify program (US). We also abide by the Employment Equity Act (Canada).
 
 
</div>

Machine Learning Engineer, Agents

Handshake

<div>
 
 Overview
 
 
 
 Handshake is recruiting exceptional graduates with a master&rsquo;s in Pharmacy (MPharm, PharmD, or equivalent) to join our AI research community. This program brings subject-matter experts together to enhance the capabilities of Large Language Models (LLMs) within specialized domains and subdomains. The Handshake AI Fellowship program runs year-round, though project availability will vary by domain.
 
 
 
 About Handshake AI
 
 
 
 About Handshake AI
 
 
 Details
 
 
 <ul>
 <li>
 The position is remote and asynchronous - work independently from wherever you are.
 </li>
 <li>
 Flexible hours and the ability to work remotely, with no minimum commitment to hours.
 </li>
 <li>
 Project work includes and is not limited to developing domain-specific prompts and evaluating LLM responses.
 </li>
 <li>
 Dedicate time researching topics that are interesting to you, with the assistance of AI.
 </li>
 <li>
 Learn new skills while contributing to the changing world of AI across various disciplines.
 </li>
 <li>
 Placement into a project will be dependent on project availability.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Must have a master's from a US institution
 </li>
 <li>
 Able to participate in primarily asynchronous work in partnership with leading AI labs.
 </li>
 <li>
 Believe your expertise can outmatch current AI systems in understanding and explaining key concepts in your field.
 
 
 </li>
 </ul>
 Selection for each project is limited to a small cohort chosen for their disciplinary and research expertise. We are seeking experts in new research areas to test the limits of the world&rsquo;s top LLMs&rsquo; scientific and language understanding by completing tasks that impact the next frontier AI model.
 
 
 Work authorization information
 
 
 F-1 students who are eligible for CPT or OPT may be eligible for projects on Handshake AI. Work with your Designated School Official to determine your eligibility. If your school requires a CPT course, Handshake AI may not meet your school&rsquo;s requirements. STEM OPT is not supported. for more information on what types of work authorizations are supported on Handshake AI.
</div>

Pharmacy Expert

PARASAIL

<div><div>Parasail is redefining AI infrastructure by enabling seamless deployment across a distributed network of GPUs, optimizing for cost, performance, and flexibility. Our mission is to empower AI developers with a fast, cost-efficient, and scalable cloud experience&mdash;free from vendor lock-in and designed for the next generation of AI workloads.</div><div>
Job Description:

The Senior Software Engineer, LLM Performance plays a crucial role in delivering a competitive platform by focusing on efficiently scheduling, executing, and managing AI workloads on distributed compute systems. This role is deeply technical, spanning from low-level GPU kernels to distributed AI orchestration and Kubernetes (K8s) deployments. It is about more than optimization; it&rsquo;s about pioneering efficient infrastructure that supports AI&rsquo;s transformative role in reshaping productivity, revolutionizing industries, and addressing some of the world&rsquo;s most challenging problems. You&rsquo;ll ensure that generative AI &mdash; including large language models (LLMs), multi-modal models, and diffusion models &mdash; operates efficiently at enterprise scale while driving continuous improvements in cost, performance, and sustainability.

Responsibilities:
<ul>
<li>Add support for new LLMs, working across the stack from low-level GPU kernels to Kubernetes-based deployments.
</li>
<li>Contribute to cutting-edge open-source LLM engines such as vLLM or SGLang to extend their capabilities and performance (e.g. use Python technologies to improve API servers or request schedulers).
</li>
<li>Operate closer to the hardware, focusing on building and integrating solutions to boost performance and hardware utilization. For example, improve attention backends like FlashAttention or FlashInfer by contributing to their development and optimization, or by integrating their solutions into vLLM.
</li>
<li>Improve LLM performance using advanced algorithmic solutions such as speculative decoding, quantization, or other state-of-the-art techniques. Understand the impact of such techniques in model quality.
</li>
</ul>Qualifications:
<ul>
<li>Expertise in GPU computing, including low-level platforms such as CUDA, ROCm, XLA, PyTorch, Jax, etc.
</li>
<li>Background in performance analysis and optimization of AI/HPC workloads (e.g. profiling or theoretical analysis of Flops and bandwidth).
</li>
<li>Experience in writing GPU kernels using technologies like CUDA, CUTLASS, Triton.
</li>
<li>Strength in Python and C++.
</li>
<li>Demonstrated contributions to open-source projects. Contributions to inference engines such as vLLM is a strong plus.
</li>
<li>A production-oriented mindset emphasizing robust, scalable code suitable for enterprise-grade applications.
</li>
<li>A relentless curiosity about cutting-edge AI technologies combined with a passion for solving complex problems.
</li>
</ul>What You Bring to the Table: We are looking for people who are eager to learn and master the lower-level compute concepts that are critical for the AI revolution. With us, your skills will not only contribute to coding but will also have a significant impact on the scalability and efficiency of AI applications at large. If you're geared up for the challenge of optimizing AI performance and eager to push our technological prowess to new heights, we're excited to welcome you aboard.</div></div>

Senior Software Engineer, LLM Performance

Prolific

<div>
 <ul>
 <li>
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 </li>
 <li>
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 </li>
 </ul>
 
 AI Trainer &ndash; Machine Learning Specialists
 
 
 
 
 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're looking for
 
 AI Trainer &ndash; Machine Learning Specialists
 
 to help train and evaluate cutting-edge AI models using real ML expertise. If you have the necessary experience, we'll send you a quick
 
 10- to 15-minute test
 
 to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models.
 
 
 Researchers looking for your skills tend to pay up to
 
 $150/hr per AI task completed
 
 . You must be prepared to complete paid tasks that require
 
 one hour of uninterrupted work
 
 , though many are shorter.
 
 
 What you'll bring
 
 
 <ul>
 <li>
 AI Training task skills and verifiable professional experience as a Machine Learning Specialist (e.g., ML engineer, data scientist, applied scientist, research engineer)
 </li>
 <li>
 A willingness to take our skills verification test to assess your suitability for our participant pool
 </li>
 <li>
 Strong attention to detail and the ability to concentrate on complex tasks for up to one hour at a time
 </li>
 <li>
 A reliable and fast internet connection and access to a computer
 </li>
 <li>
 A willingness to self-declare your earnings, as our participants are self-employed
 </li>
 <li>
 A Paypal account to receive payment from our clients
 
 
 </li>
 </ul>
 
 What you'll be doing in the role
 
 
 
 <ul>
 <li>
 Completing AI training tasks such as analyzing, editing, and writing annotations (including technical reasoning and structured evaluation)
 </li>
 <li>
 Judging the performance of AI in performing ML-relevant tasks (e.g., model/experiment critique, data leakage detection, metrics interpretation, debugging approach, methodology review)
 </li>
 <li>
 Improving cutting-edge AI models by providing expert feedback on correctness, robustness, clarity, and technical depth
 
 
 </li>
 </ul>
 
 Key Technologies
 
 
 
 <ul>
 <li>
 General AI Training
 </li>
 <li>
 Model Evaluation and Evals
 </li>
 <li>
 Trust and Safety
 </li>
 <li>
 Red Teaming
 </li>
 <li>
 Quality Analytics
 </li>
 <li>
 Data/ML Concepts (e.g., supervised learning, deep learning, NLP, CV, statistics, experimentation)
 
 
 </li>
 </ul>
 
 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 machine learning 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 breath 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 Training - Machine Learning Specialist (PST)

MERCOR

<div>About the job
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
Position: Life Sciences AI Specialist 
Type: Contract 
Compensation: $73/hour 
Location: Remote
Role Responsibilities<ul><li>
Write and refine prompts to guide model behavior in the life sciences context.</li><li>
Evaluate LLM-generated responses to biology-related queries for scientific accuracy and reasoning quality.</li><li>
Conduct fact-checking using authoritative public sources and domain knowledge.</li><li>
Annotate model responses by identifying strengths, areas of improvement, and factual or conceptual inaccuracies.</li><li>
Assess clarity, structure, and appropriateness of explanations for different audiences.</li><li>
Apply consistent evaluation standards by following clear taxonomies, benchmarks, and detailed evaluation guidelines.</li></ul>
Qualifications
Must-Have<ul><li>
PhD in Biology or a closely related life sciences field.</li><li>
Deep expertise in Molecular &amp; Cellular Biology, Organismal Physiology &amp; Development, Microbiology, Immunology &amp; Pathobiology, or Ecology, Evolution &amp; Environmental Biology.</li><li>
Significant experience using large language models (LLMs).</li><li>
Excellent writing skills and ability to explain complex life sciences concepts.</li><li>
Strong attention to detail.</li><li>
Experience reviewing or editing technical or academic writing.</li></ul>
Preferred<ul><li>
Prior experience with RLHF, model evaluation, or data annotation work.</li><li>
Experience teaching, mentoring, or explaining life sciences concepts to non-expert audiences.</li><li>
Familiarity with evaluation rubrics, benchmarks, or structured review frameworks.</li></ul>
Application Process (Takes 20&ndash;30 mins to complete)<ul><li>
Upload resume</li><li>
AI interview based on your resume</li><li>
Submit form</li></ul>
Resources &amp; Support<ul><li>
For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome/welcome</li><li>
For any help or support, reach out to: support@mercor.com</li></ul>
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.</div>

Research Associate, Biological Sciences

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