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research scientist

Prolific

<div>
 
 AI Trainer &ndash; Research Scientists
 
 
 
 
 
 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&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.
 
 
 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.
 
 
 
 
 What you&rsquo;ll be doing in the role
 
 
 
 
 Completing AI training tasks such as analyzing, editing, and writing research-focused content
 
 
 Judging the performance of AI on research design, methodology, and scientific reasoning prompts
 
 
 Improving cutting-edge AI models using your experience in research and experimentation
 
 
 
 
 What you&rsquo;ll bring
 
 
 
 
 Experience working as a Research Scientist or in a closely related research role
 
 
 A strong understanding of scientific methodology, experimental design, and data analysis
 
 
 A willingness to take our skills verification test to assess your suitability for our Domain Expert participant pool
 
 
 Strong attention to detail and the ability to concentrate on complex tasks for up to one hour at a time
 
 
 A reliable and fast internet connection and access to a computer
 
 
 A Paypal account to receive payment from our clients*
 
 
 
 
 Why Prolific is a great platform to join as a Domain Expert participant
 
 
 
 
 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.
 
 
 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.
 
 
 <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.
 
 
 </li>
 </ul>
 
 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 information.
</div>

AI Training - Research Scientist (PST)

Handshake

<div>
 
 About Handshake
 
 
 
 Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.
 
 
 
 Why Join Handshake Now
 
 
 
 <ul>
 <li>
 Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel
 </li>
 <li>
 Work hand-in-hand with world-class AI labs, Fortune 500 partners and the world&rsquo;s top educational institutions
 </li>
 <li>
 Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others
 </li>
 <li>
 Build a massive, fast-growing business with billions in revenue
 
 
 </li>
 </ul>
 
 About The Role
 
 
 
 Untangling the science of Data &amp; Evaluations for Frontier AI
 
 
 Thanks to our massive network of the world&rsquo;s top experts in all domains, the demand for human data from Handshake AI has exploded (with revenue growing from 0 to well over 9-figures in the first year and growth only accelerating since). Now the world&rsquo;s top AI Labs are looking to Handshake for advice on how to leverage human expertise to make frontier models more useful for everyone, and we are forming a leading research group to advance the science of Data and Evaluations for AI.
 
 
 
 You Will
 
 
 
 <ul>
 <li>
 Publish papers, open source software, and do bleeding-edge open science on AI agents, LLMs and frontier multimodal models, RL environments, post-training.
 </li>
 <li>
 Work with all of the top AI Labs in the world and understand/shape what their researchers are prioritizing (uniquely, you get to work on research at a company whose customers are top AI researchers)
 </li>
 <li>
 Create public benchmarks that meaningfully measure AI progress, leveraging thousands of the world&rsquo;s top experts in different domains from the Handshake network to construct the most representative/high-quality benchmark.
 </li>
 <li>
 Shape the frontier of AI through high-impact research on topics that matter: how to measure/value data, how to effectively evaluate AI, what shapes of data are most effective as AI advances, what makes effective training/RL environments, post-training data recipes.
 
 
 </li>
 </ul>
 
 Desired Capabilities
 
 
 
 <ul>
 <li>
 Based in San Francisco, and excited to work in the office.
 </li>
 <li>
 Ph.D. in ML/AI, data science, or related fields.
 </li>
 <li>
 Publications in top AI/ML venues like NeurIPS, ICML, ICLR.
 </li>
 <li>
 Builders who love to tinker with LLMs/Agents and ship high-quality software, benchmarks/datasets, research, blogs.
 
 
 </li>
 </ul>
 
 Perks
 
 
 
 Handshake delivers benefits that help you feel supported&mdash;and thrive at work and in life.
 
 
 
 
 The below benefits are for full-time US employees.
 
 
 
 
 🎯
 
 Ownership:
 
 Equity in a fast-growing company
 
 
 💰
 
 Financial Wellness
 
 : 401(k) match, competitive compensation, financial coaching
 
 
 🍼
 
 Family Support:
 
 Paid parental leave, fertility benefits, parental coaching
 
 
 💝
 
 Wellbeing:
 
 Medical, dental, and vision, mental health support, $500 wellness stipend
 
 
 📚
 
 Growth:
 
 $2,000 learning stipend, ongoing development
 
 
 💻
 
 Remote &amp; Office:
 
 Internet, commuting, and free lunch/gym in our SF office
 
 
 🏝
 
 Time Off:
 
 Flexible PTO, 15 holidays + 2 flex days, winter #ShakeBreak where our whole office closes for a week!
 
 
 🤝
 
 Connection:
 
 Team outings &amp; referral bonuses
 
 
 Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.
 
 
 Compensation Range: $320K - $365K
 
 
</div>

AI Research Scientist

Google

<div>Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.<h3 class="jobSectionHeader">
Minimum qualifications:</h3><ul>
<li>Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field, or equivalent practical experience.</li>
<li>5 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases, or statistical analysis, or 3 years of experience with a PhD degree.</li>
<li>4 years of experience in data analysis or related fields as a statistician or data scientist.</li>
<li>Experience with statistical software (e.g., R, Python, MATLAB, pandas) and database languages (e.g., SQL).</li>
<li>Experience with statistical methodologies.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>PhD degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.</li>
<li>8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree. 
</li>
<li>Experience in training, validating or optimizing language models or LLM-based classifiers.</li>
<li>Experience analyzing multi-modal data (image, audio, or video).</li>
<li>Experience of GenAI safety and red-teaming.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
User Protection is an organization dedicated to protecting Google's users from abuse, account compromise and other harms online. Our team works with the Content Safety (CS) and User Protection Platform and Services (UPS) which develops tools to protect users from abusive content at scale, often leveraging AI technology to do so. Our team provides data science capabilities to these two organizations, and works directly with product and engineering to evaluate, understand, and improve the quality of our protections. Organizationally, we are a part of a large data science team in Core, which provides ample opportunities for knowledge sharing, development, and learning from other data scientists working in adjacent domains. 
 
CS and UPS equip Google products with tools to protect users from abuse and harm. As a Data Scientist working with CS and UPS, you'll be helping to evaluate, understand, and improve our abuse protections - which are generally built with and for AI tools. We work closely with cross-functional product teams on specific content safety classifiers, but also on generic strategies and tooling for understanding content safety classifiers. 
 
Our team is designing safety data evaluations and safety mitigation evaluations, including LLM-as-judge, prompt injection, and Responsible AI testing. We also work with flagship GenAI product teams on understanding Google-wide GenAI safety postures in production traffic.The US base salary range for this full-time position is $174,000-$252,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.<div></div><div> 
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.</div></div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Solve ambiguous problems in the Generative Artificial Intelligence safety space, including agent-based safety. 
</li>
<li>Develop quantitative methodologies to curate training data and evaluation data from synthetic data and real-world production data for improving content safety mitigations. Design and evaluate models to mathematically express and solve defined problems with limited precedent.</li>
<li>Drive cross-functional alignment on measuring violation rates and unjustified refusals across multiple flagship Generative Artificial Intelligence product surfaces. Identify and clarify business or product questions.</li>
<li>Provide feedback and refine business questions into tractable analysis, evaluation metrics, or mathematical models. Drive clarity and coherence in understanding safety at scale across Google.</li>
<li><div>Own the process of gathering, extracting, and compiling data across sources (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.</div></li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Senior Research Data Scientist, Core Safety Data Science

OpenAI

About the Team
 
The Alignment Science team at OpenAI studies the science of intent alignment: how to train models to understand what users are actually asking for, act faithfully on that intent while respecting safety constraints, verify what they did, and report their limitations honestly. Our work sits alongside broader value alignment efforts, but this team focuses on scalable methods for ensuring instruction-following, honesty, and robustness as models become more capable.
 
We work on both sides of alignment research: producing externally publishable results and integrating promising techniques into the models OpenAI deploys. Recent team research on model confessions studies how models can be trained to honestly report shortcomings after their original answer, including failures involving hallucination, instruction following, scheming, and reward hacking. That work reflects a broader agenda: build scalable and general methods to ensure models follow human intent.
 
The team uses a mix of training and evaluation methods, with a focus on reinforcement learning. We care about rigorous, quantitative research that can translate into safer model behavior.
 
About the Role
 
As a Research Engineer / Research Scientist on the Alignment team, you will design and run experiments that help increasingly capable models follow user intent, remain calibrated about correctness and risk, and honestly surface their own mistakes. You will work on hands-on model training, evaluation design, and research infrastructure, while helping turn promising alignment methods into techniques that can be used in frontier model development.
 
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. We are also open to exceptional remote candidates who can operate independently and collaborate closely with the team.
 
In this role, you will: 
Design and implement alignment experiments focused on intent following, honesty, calibration, and robustness.
 
Train and evaluate models using reinforcement learning, and other empirical ML methods.
 
Develop evaluations for failure modes such as hallucination, instruction-following failures, reward hacking, covert actions, and scheming.
 
Study methods that encourage models to verify their behavior and report shortcomings honestly, including confession-style training objectives.
 
Build monitoring and inference-time interventions that ensure compliant behavior or surface model issues to users or downstream systems.
 
Investigate how alignment methods scale with model capability, compute, data, context length, action length, and adversarial pressure.
 
Integrate successful techniques into model training and deployment workflows.
 
Produce externally publishable research when results advance the broader science of alignment.
 
Collaborate with researchers and engineers across post-training, RL, evaluations, safety, and product-facing teams.
 
You might thrive in this role if you: 
Have strong hands-on experience training, evaluating, or debugging large ML models, especially LLMs.
 
Have excellent engineering skills in Python and modern ML frameworks such as PyTorch.
 
Bring mathematical rigor, quantitative taste, and comfort turning ambiguous research questions into measurable experiments.
 
Have experience with reinforcement learning, post-training, preference optimization, scalable oversight, model evaluation, or adjacent empirical ML research.
 
Can operate with high independence and do not need close day-to-day handholding.
 
Enjoy fast-paced, collaborative research environments where priorities shift as models and evidence change.
 
Have a strong record in technical problem solving, such as competitive programming, math contests, systems work, or similarly rigorous engineering and research projects.
 
Care about building AI systems that are trustworthy, honest, and reliable in high-stakes settings.
 
Are motivated by making concrete progress on alignment methods that can be tested, trained, published, and deployed.
 
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
 
$250K – $445K + Offers Equity

Researcher, Alignment Science

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
We are seeking a Senior Applied Scientist to build production machine learning systems that solve complex business problems at scale. You will design, develop, and deploy ML solutions that directly impact millions of users and drive strategic decision-making across the organization. 
 
In this role, you will work on challenging problems spanning predictive modeling, natural language processing, recommendation systems, and generative AI applications. You will collaborate with cross-functional teams to translate ambiguous business challenges into rigorous technical solutions. 
 
Key job responsibilities 
<ul><li>Design and deploy large-scale machine learning systems in production environments</li><li>Develop innovative ML solutions using state-of-the-art techniques including deep learning, NLP, and generative AI</li><li>Create ML solutions that standardize and optimize manager-employee interactions, providing intelligent suggestions and establishing metrics to measure engagement quality across diverse conversation types</li><li>Partner to build causal inference models and experimental frameworks to measure impact</li><li>Collaborate with product managers, engineers, and business leaders to define technical roadmaps</li><li>Communicate complex technical concepts to diverse audiences, from technical peers to senior leadership</li></ul> 
About the team 
The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>PhD, or Master's degree and 5+ years of applied research experience</li><li>3+ years of building machine learning models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience with large scale distributed systems such as Hadoop, Spark etc.</li><li>Proven track record of leading end-to-end development from Ideation to monitoring in production</li><li>Proven track record of mentoring and growing junior and mid-level scientists</li><li>Experience with building LLMs, generative AI applications on AWS</li><li>Excellent communication skills with ability to influence senior leadership</li><li>Demonstrated ability to work in ambiguous problem spaces with evolving requirements</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, San Francisco - 192,200.00 - 260,000.00 USD annually 
USA, MA, Boston - 167,100.00 - 226,100.00 USD annually 
USA, VA, Arlington - 167,100.00 - 226,100.00 USD annually 
USA, WA, Bellevue - 167,100.00 - 226,100.00 USD annually 
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div>

Senior Applied Scientist, PXT Central Science

THRAD

<div><h3 class="jobSectionHeader">The Role</h3>
We are looking for an Applied Scientist to own the models that decide which ad appears in which AI conversation, in real time, across millions of queries a day. Ad selection inside LLM chats is a genuinely new problem: no click history, no cookies, no page context. Just an evolving conversation and a few hundred milliseconds to make a decision that has to feel native to the user, relevant to the advertiser, and profitable for the publisher.
This is a research role with a production mandate. Your models go live, not into a paper. You will work directly with our CTO and the founding engineering team on the systems powering millions of ads a day across Fortune 500 campaigns.<h3 class="jobSectionHeader">
Core Tech Stack</h3><ul><li>
ML: PyTorch, embedding-based retrieval, modern transformer architectures</li><li>
Backend: Python (FastAPI), async serving, real-time inference</li><li>
Data: PostgreSQL for transactional, ClickHouse for analytics and event data</li><li>
Infra: AWS, Docker, CI/CD</li><li>
Plus: whatever the problem demands. We pick tools that ship.</li></ul><h3 class="jobSectionHeader">
Example Projects</h3><ul><li>
Design and train contextual ad relevance models for LLM conversations, from retrieval through ranking through creative selection.</li><li>
Build efficient algorithms for real-time bidding and auction mechanics, balancing publisher yield and advertiser ROAS.</li><li>
Productionize regression models to predict downstream conversion from early conversational signals.</li><li>
Apply privacy-preserving clustering methods to categorize conversational context and improve advertiser targeting without compromising user data.</li><li>
Run live experiments against real traffic on our publisher network. Iterate on CTR, ROAS, and conversation quality metrics.</li><li>
Own the evaluation framework for ad quality, relevance, and user experience across the marketplace.</li><li>
Read an ArXiv paper on Monday. Have a prototype running on Friday.</li></ul><h3 class="jobSectionHeader">
What You Will Do</h3><ul><li>
Own the research and shipping of the models powering ad selection across Thrad's network.</li><li>
Move research to production end to end: hypothesis, training, evaluation, deployment, monitoring.</li><li>
Collaborate directly with the CTO and co-founders to translate research direction into working systems, often within the same day.</li><li>
Partner with the Data and Product teams to design and analyze live experiments on real traffic.</li><li>
Contribute to system architecture decisions as we scale from millions to billions of daily ad impressions.</li><li>
Communicate findings clearly to both technical and non-technical audiences across the team.</li></ul><h3 class="jobSectionHeader">
Who You Are</h3>
Must-haves<ul><li>
2 to 5 years of applied ML experience, ideally in ads, search, recommendations, ranking, or NLP.</li><li>
An advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related field &mdash; or equivalent experience shipping production ML.</li><li>
Strong fundamentals in mathematical and statistical modeling. You know why your model works, not just that it does.</li><li>
Fluent in PyTorch, modern transformer architectures, and embedding-based retrieval.</li><li>
Strong Python, comfort with distributed training and inference.</li><li>
You have shipped ML to production at scale. Not just notebooks.</li><li>
You enjoy identifying and owning hard, open-ended problems. You form testable hypotheses and run them to ground.</li><li>
Based in San Francisco or willing to relocate. This is an in-person role at our SF HQ.</li></ul>
Nice-to-haves<ul><li>
Experience with RLHF, preference modeling, or LLM fine-tuning.</li><li>
Background in auction theory, bidding systems, real-time pricing, or yield optimization.</li><li>
Prior work at an ad-tech, search, recommendations, or marketplace company.</li><li>
Published research at NeurIPS, ICML, ACL, KDD, RecSys, or equivalent.</li><li>
Familiarity with ClickHouse or other column-oriented OLAP databases for analytical workloads.</li><li>
A relentless interest in the AI and LLM ecosystem and how advertising will evolve inside conversational interfaces.</li></ul><h3 class="jobSectionHeader">
Why Thrad</h3><ul><li>
First mover: We are defining a new category. Paid ads in AI is an inevitable market and we are building the infrastructure for it.</li><li>
Real traction: Fortune 500 clients, millions of daily impressions, and publisher partners across the AI web, all pre-seed.</li><li>
Research with teeth: Your work ships. Your models run in production against real traffic with real revenue on the line.</li><li>
Direct impact: Small founding team. Your decisions shape the models, the product, and the company.</li><li>
Ownership: Meaningful equity in a company at the intersection of two massive markets: AI and ad tech.</li><li>
Craft: A team that cares about shipping quality, not just quantity.</li></ul><h3 class="jobSectionHeader">
How to Apply</h3>
Send your CV and a brief note on what excites you about building at the intersection of AI and advertising. If you have published work, a GitHub, or models you have shipped that you are proud of, include them. We read every application.</div>

Applied Scientist

Gladstone Institutes

<div><h2 class="jobSectionHeader">Category:
</h2>Science
<h2 class="jobSectionHeader"> 
Lab/Area:
</h2>Alexanian Lab
<h2 class="jobSectionHeader">Description:
</h2>Who we are:
The Gladstone Institutes is a distinguished independent, not-for-profit research institution dedicated to advancing human health through cutting-edge medical research and education. Our work spans neuroscience, cardiovascular biology, immunology, and stem cell biology, with a focus on overcoming disease. With a team of approximately 600 members, including renowned leaders in science and biomedicine, Gladstone operates across five institutes, alongside various centers and programs. Located at the Mission Bay Campus in an award-winning building, Gladstone offers competitive salaries and benefits, providing an optimal environment for individuals to realize their full potential and make a meaningful impact on global health
About the role: 
 
Are you excited about uncovering the molecular mechanisms that drive cellular behavior&mdash;and how these processes go awry in disease? The Alexanian Lab at the Gladstone Institutes is looking for a curious and motivated Research Associate (RA) to join our growing team!
We are a new lab dedicated to understanding the gene-regulatory and epigenetic mechanisms that govern cellular plasticity in both normal and disease contexts, with a particular focus on heart disease. Our long-term goal is to uncover insights that can inform new therapies targeting gene regulation in chronic diseases characterized by harmful changes in cell behavior and tissue structure.
What you will do: 
 
As a Research Associate, you will work closely with the team on a range of exciting and interdisciplinary projects. Your responsibilities will include:
<ul><li>Molecular biology techniques: cloning, plasmid DNA prep, PCR, gel electrophoresis, RNA isolation, qRT-PCR, chromatin immunoprecipitation
</li><li>Cell culture: work with primary cells and human stem cells, transfection, and virus production
</li><li>Genomic technologies: gain hands-on experience with cutting-edge tools like single-cell RNA-seq and ATAC-seq, CRISPR-based screening, CUT&amp;RUN, and PRO-seq
</li><li>Computational biology and AI: support analysis of large-scale genomic datasets, contribute to data processing and visualization, and participate in projects using machine learning models to understand cell states and predict gene regulatory programs
</li><li>Animal work: mouse colony management, genotyping, dissections, and breeding design
 
Lab operations: help maintain lab function through ordering, supply management, and equipment upkeep
</li></ul>What you will need:
<ul><li>BA/BS degree in related field
</li><li>Excellent teamwork, organizational, communication, and time-management skills
</li><li>Team worker
</li><li>Highly self-motivated, reliable and responsible.
</li><li>Excellent organizational and interpersonal communication skills (verbal and written)
</li><li>Willingness and ability to learn new skills and explore
</li><li>Ability to work independently and as a member of a research team
</li><li>Excellent organization and time management skills
</li><li>Attention to detail in experimental techniques and record keeping.
</li><li>1+ years wet lab experience (in addition to lab coursework), preferred 
</li></ul> 
Why join us:
This position is ideal for recent graduates considering graduate or medical school, or for candidates looking to gain in-depth experience in a dynamic academic research environment. RAs in our lab are considered full scientific contributors&mdash;they are expected to take ownership of their projects, drive experiments independently, help shape the direction of the research, and publish their work.
The Alexanian Lab is a collaborative team committed to mentorship, creativity, scientific curiosity, and fostering an inclusive environment. The lab is part of the vibrant research community on the Gladstone&ndash;UCSF Mission Bay campus, offering rich opportunities for learning and collaboration.
What to include:
Resume / cover letter
***We are ideally looking for a candidate to start in summer 2026, but we can accommodate a later start date for the right person.
Salary Range:
$28.35/hr. - $32.21/hr. 
 
Gladstone Perks &amp; Benefits
<ul><li>People &ndash;work with talented, committed, and supportive teammates within an organization that values each member of its community.
</li><li>A meaningful place to grow and learn &ndash;whether it&rsquo;s your professional skills or scientific knowledge, we have the resources and environment to advance either so you can better support Gladstone&rsquo;s mission to drive a new era of discovery in disease-oriented science and to mentor tomorrow&rsquo;s leaders in an inspiring and excellent environment.
</li><li>Healthy work/life balance &ndash;you are highly engaged and productive at work because you can have time to recharge and enjoy a vibrant life outside of work.
</li><li>Compensation &ndash;competitive salary. Title and salary will be commensurate with education and experience.
</li><li>Excellent benefits &ndash;generous medical, dental, vision, retirement plan, paid vacation, commuter benefits, access to free shuttle transportation. 
 
</li></ul>Gladstone is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, sex, religion, national origin, ancestry, age, marital status, medical condition, physical or mental disability, veteran status, sexual orientation, or any other non-job related characteristic. We make all employment decisions so as to further this principle of equal employment.</div>

Research Associate I- Alexanian Lab

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