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Valence

<div>Valence has built the only first-to-market AI native coaching platform for enterprise, offering personalized, expert, and human-like guidance and support to any leader or employee. We&rsquo;re not just talking about the future of work &mdash; we&rsquo;re building it now, with the most innovative Fortune 500 companies across healthcare, financial services, manufacturing, and technology.
Learn more about our work with Microsoft: Valence Brings AI Coaching More Deeply Into the Flow of Work with Microsoft 365
Our focus is on the problems that actually decide whether AI changes how organizations operate &mdash; the ones with no playbook, no obvious answers, and no guarantee of success. If you want to be part of the small group that defines how AI transforms the future at a global scale, this is your chance.
And this isn&rsquo;t for everyone. We&rsquo;re not looking for people who want predictability or incremental progress. We only want those who are restless at the edge of what&rsquo;s possible, who get bored when things feel &ldquo;done,&rdquo; and who are driven to redefine what AI can mean for leaders, companies, and the world. Because at Valence, the work worth doing is the kind that redefines work itself.<div></div> 
The Role
As a Platform Engineer at Valence, you will build and operate the secure, reliable, and scalable foundation that lets every product and AI team ship Nadia innovations faster and with lower risk. Platform Engineering is Valence's force multiplier: we own the shared control planes for trust and safety, global access and routing, LLM governance, deployment automation, workload isolation, observability and SLOs, and AI-native engineering execution.
Your mandate is simple: increase shipping velocity and customer trust at the same time, by making the safe path the default path. You'll build the paved roads every team uses in production, and enforce minimum production standards through templates, CI/CD gates, scorecards, and time-bound exceptions, so every service is observable, reversible, and secure by default.
We don't expect any one candidate to check every technical box, but we do look for engineers who are eager to learn, iterate rapidly, and contribute across challenges that span reliability, security, global delivery, and developer experience.<div></div> 
About Valence
We're the only company pioneering leadership coaching for large enterprises in an AI-first way. Our mission is to transform how the world's biggest companies approach learning and development, helping teams work better together through AI-powered personalization that adapts to individual goals and organizational culture using the latest advances in machine learning and natural language processing.<div></div> 
We've been featured in Harvard Business Review, TIME, World Economic Forum, Financial Times, Forbes and an Inc. 5000 fastest-growing private companies in America. Our clients represent the most diverse and sophisticated enterprise AI implementations globally, including Coca-Cola, Delta, Nestl&eacute;, General Mills, Schneider Electric, Deutsche Telekom, AstraZeneca, Prudential, CVS and Bristol Myers Squibb.<div></div> 
Working at Valence means you'll work directly with Fortune 500 technology leaders, building expertise through the most complex enterprise deployments while gaining insight into diverse organizational approaches to AI transformation. These aren't just any enterprise clients - they're the companies defining what AI-first business transformation looks like across every major industry.
What You'll Do<ul><li>
Build the paved roads. Design and operate shared platform primitives used by multiple teams (authorization and routing guardrails, secure logging, rollout controls, observability, queue infrastructure, and the centralized LLM gateway) so teams build on standards instead of reinventing them.</li><li>
Make change safe by default. Own the reliability and change-safety systems that let the org move fast without breaking trust: CI/CD gates, migration safety patterns, progressive delivery, rollback automation, and kill switches.</li><li>
Enforce security at the platform layer. Ship secure defaults, policy enforcement frameworks, auditability, and data-access guard libraries so the safe path is the easy path.</li><li>
Run global delivery controls. Implement single-domain strategy, region pinning and routing, residency-aware behavior, and cross-region config consistency checks for enterprise customers worldwide.</li><li>
Raise the operational bar. Establish SLOs, synthetic checks, alerting standards, and incident runbooks and drills that drive faster detection and recovery.</li><li>
Build the internal developer platform. Create service templates, blessed internal-tool paths, and standard deploy, monitoring, and auth patterns that make the right thing the default thing.</li><li>
Operate an AI-native engineering plane. Build issue-to-PR automation infrastructure with governance, human-in-control workflows, and audit logs that convert signals into auditable, human-approved execution outcomes.</li></ul>
What We're Looking For<ul><li>
Technical foundation: 8+ years of experience in software engineering, distributed systems, infrastructure, or platform/SRE roles, with a track record of building systems other teams depend on.</li><li>
Platform mindset: You build reusable primitives, not one-off features. You think in terms of paved roads, secure defaults, and standards that scale across many teams.</li><li>
Reliability and change-safety expertise: Hands-on experience with CI/CD, progressive delivery, rollback and migration safety, observability, SLOs, and incident response.</li><li>
Cloud &amp; deployment experience: Comfortable developing and operating services in cloud environments (AWS, GCP, Azure) and working with containerization and orchestration (Docker, Kubernetes).</li><li>
Security &amp; compliance awareness: Familiarity with implementing platform-level guardrails (authorization, auditability, data-access controls, and policy enforcement) in a privacy- and residency-conscious way.</li><li>
Engineering excellence: Strong software engineering skills, including writing maintainable code, debugging distributed systems, and collaborating in cross-functional teams.</li><li>
Growth orientation: Eagerness to tackle unfamiliar problems, learn new technologies, and shape our platform and culture.</li><li>
Communication: Ability to explain technical ideas clearly and work effectively with both technical and non-technical stakeholders.</li></ul>
What You'll Get<ul><li>
Ownership &amp; Rapid Growth</li><li>
Outsized missions from day one, with direct responsibility for company-defining projects</li><li>
Work alongside the executive team with transparency into strategy and decision-making</li><li>
Influence on direction through real-time customer feedback and market insights</li></ul><div></div><ul><li> 
AI-First Operator</li><li>
Work directly with cutting-edge AI models and next-generation platforms</li><li>
Build expertise in enterprise AI implementation across Fortune 500 companies and multiple industries</li><li>
Establish yourself as a recognized leader among peers in shaping how AI transforms work at a global scale</li></ul><div></div><ul><li> 
Compensation</li><li>
Competitive salary including base + bonuses</li><li>
Comprehensive health coverage (medical, dental, vision) from day one</li><li>
Generous PTO, company-wide R&amp;R shutdowns, and paid parental leave</li><li>
Retirement plan support for US and global employees</li></ul><div></div><ul><li> 
Equity</li><li>
Meaningful ownership in a venture-backed company at a growth inflection point</li><li>
Financial upside that comes from scaling fast</li><li>
Top-up grants as we scale and you deliver exceptional performance &mdash; your compensation grows alongside your impact</li></ul><div></div><ul><li> 
Top-Performing Culture</li><li>
A culture built for top talent: intensity to win, growth without limits, and a team that solves hard problems and celebrates big wins together</li></ul><div></div> 
Learn more about us and meet our team here
Location and Work Environment
If candidates are based in NYC or Toronto they can work hybrid in our offices, otherwise this role can be remote. Candidates must be comfortable working with colleagues in different time zones (UK), and have valid travel documents without work authorization restrictions in the US.<div></div> 
Diversity and Inclusion
We are dedicated to creating a diverse and inclusive environment where everyone feels valued and supported. We encourage applications from candidates of all backgrounds and offer accommodations upon request throughout the hiring process. If you have any questions, please reach out to Allison Langille, Head of People, at jobs@valence.co.<div></div> 
Employment Verification &amp; Commitment
We use third-party services to verify employment history, education, and other information relevant to your candidacy. Employment is contingent upon the successful completion of these verification checks. This is a full-time role that requires a high level of focus, availability, and commitment. Employees may not hold concurrent full-time employment with another organization while employed at Valence. Any outside consulting, advisory, freelance, or other professional work must be disclosed and approved in advance and must not interfere with job responsibilities, availability, performance, or create a conflict of interest - including risks related to confidentiality, intellectual property, or competition.
Valence is committed to protecting the privacy of all applicants. Information you submit will be used for recruiting, evaluation, legal compliance, and recordkeeping purposes only. We do not require access to personal account credentials at any stage of the hiring process. For more information, see our Candidate Privacy Notice.<div></div> 
#LI-HYBRID</div>

Staff Software Engineer, Platform

Tamarind Bio

<div><h1 class="jobSectionHeader">About Tamarind Bio</h1>
We enable any scientist to access AI-powered drug discovery. Thousands of scientists from large pharma companies, top biotechs, and academic institutions use Tamarind to design protein drugs, improve industrial enzymes, and create cutting edge molecules that weren&rsquo;t feasible until now.
New AI models are quickly eclipsing physics-based tools in computational drug discovery. Scientists often struggle to fine-tune, deploy, and scale these models, leaving breakthroughs on the table. Tamarind provides a simple interface to the vast array of tools being released daily.
Staff Software Engineer / Technical Lead
We're hiring a Staff Software Engineer to provide technical leadership across our engineering team as we continue to scale the platform behind Tamarind.
Today, our engineering team consists primarily of early and mid-career engineers. As the complexity of our systems and customer requirements continues to grow, we're looking for someone who can help guide technical decision-making, mentor engineers, and drive architectural discussions across the organization.
This is not an engineering management role.
We're looking for a hands-on technical leader who enjoys writing code, reviewing designs, solving difficult engineering problems, and helping other engineers grow. You'll work closely with the CTO to shape technical direction while remaining deeply involved in execution.
The role spans architecture, infrastructure, product development, code reviews, technical mentorship, and engineering best practices.
What You'll Do<ul><li>
Partner with the CTO on architecture, technical planning, and major engineering initiatives</li><li>
Provide technical guidance across a team of 7-8 engineers</li><li>
Lead design reviews and architectural discussions</li><li>
Help engineers navigate complex technical challenges</li><li>
Contribute directly to the codebase across infrastructure, backend services, APIs, and product development</li><li>
Review code and provide feedback on implementation approaches</li><li>
Identify opportunities to improve reliability, scalability, performance, and developer productivity</li><li>
Support technical decision-making across new products and platform capabilities</li><li>
Work closely with customers and internal stakeholders to understand requirements and translate them into practical solutions</li><li>
Help establish engineering standards as the team continues to grow</li></ul>
Week in the Life<ul><li>
Collaborate with the CTO on technical priorities and architectural decisions</li><li>
Review designs and provide guidance on implementation approaches</li><li>
Build and operate services across infrastructure, ML systems, APIs, and customer-facing applications</li><li>
Participate in code reviews and technical discussions</li><li>
Help unblock engineers working through difficult technical problems</li><li>
Work directly with customers to understand requirements and gather feedback</li><li>
Balance hands-on engineering work with technical leadership responsibilities</li></ul>
Ideal Qualifications<ul><li>
7+ years of software engineering experience</li><li>
Experience serving as a senior technical contributor, staff engineer, principal engineer, or technical lead</li><li>
Strong software architecture and distributed systems experience</li><li>
Experience building and operating production infrastructure and cloud services</li><li>
AWS experience (EC2, S3, DynamoDB, Docker, etc.)</li><li>
Ability to mentor engineers and provide technical guidance across multiple projects</li><li>
Strong communication skills and sound engineering judgment</li><li>
Comfort operating in an early-stage startup environment</li><li>
Willingness to work onsite in San Francisco</li></ul>
Technology
Our technology sits at the intersection of DevOps, MLOps, and Computational Biology. We support workloads ranging from large-scale ML inference and model deployment to workflow orchestration across research, infrastructure, and scientific computing environments.
The role requires someone who enjoys moving between architecture, implementation, operations, and mentorship while helping a growing engineering team tackle increasingly complex technical challenges.
Compensation Range: $150K - $250K</div>

Staff Software Engineer / Technical Lead

Apple

The Apple Services Engineering AI/ML organization is hiring a Machine Learning Engineer to join the Search team for Video catalog. 
 
Our team builds the core intelligence that powers search discovery experiences in the Apple TV App, Siri, and Spotlight cross platforms, helping users effortlessly find and enjoy the content they love. We are a collaborative, high-impact team that values innovation, craftsmanship, and end-to-end ownership from idea to launch. Our systems combine large-scale data, modern retrieval and ranking models, and a deep commitment to user privacy. 
 
Join us, you&rsquo;ll develop scalable systems and machine learning models that drive search relevance, personalization, and understanding of content at scale. Working closely with cross-functional partners in product and design, you&rsquo;ll translate cutting-edge research in advanced machine learning and generative AI into secure and delightful production features used by millions every day. 
 
Description 
 
As a Machine Learning Engineer on the Video Search team, within the Apple Services Engineering AI/ML organization, you will design and deploy large-scale ML systems that power search and discovery across Apple platforms. 
 
You&rsquo;ll apply machine learning, natural language understanding, and generative AI to model user intent and deliver relevant, personalized results. Your work will involve building and optimizing cutting edge data processing, ML models, retrieval pipelines, and ranking systems that operate at global scale and under strict privacy standards. 
 
This is a hands-on role where you will collaborate closely with cross-functional teams to bring advanced ML technologies into production-shaping how users discovery content they love in Apple TV app, cross Apple TV partners on Apple Platforms, also through Siri and Spotlight.&quot;,&quot;responsibilities&quot;:&quot;Solve complex research problems and implement solutions from concept to execution. 
 
Design and implement retrieval and ranking systems using semantics and user context. 
 
Build and deploy ML, NLP and LLM models to improve search relevance and personalization. 
 
Analyze data and model performance to identify opportunities for search quality enhancement. 
 
Develop automated tests for continuous integration and ensure successful production deployment. 
 
Conduct A/B tests to measure search improvements. 
 
Collaborate with cross-functional teams to innovate intelligent video catalog text search. 
 
Enhance search recall and ranking for global Apple devices across all platforms and languages. 
 
Utilize big data tech to evaluate content discovery features. 
 
Ensure systems meet Apple&rsquo;s privacy, efficiency, and user experience standards. 
 
Preferred Qualifications 
 
Experience with search or recommendation systems, and semantic retrieval or vector databases. 
 
Expertise in transformer architectures, embeddings, and retrieval or ranking models. 
 
Experience in applying or fine-tuning LLMs for understanding and generation tasks. Familiarity with prompt design, context management, RAG and Agentic architectures and solutions. 
 
Exposure to evaluation and safety frameworks for LLM-based systems. 
 
Knowledge of reinforcement learning and other modern post training practices for LLMs. 
 
Passion for developing intelligent, human-centered experiences to enhance content discovery. 
 
Minimum Qualifications 
 
Experience in machine learning, NLP, IR, or more recently Large Language Model ( LLMs). 
 
Strong programming skills in Python, Java and Go for building scalable ML systems. 
 
Hands-on expertise in ML libraries such as PyTorch, JAX, TensorFlow for model training and deployment. 
 
Ability to translate product goals into technical solutions, improving user experience. 
 
Strong communication, collaboration, and analytical problem-solving skills. 
 
In-depth knowledge of search and information retrieval fundamentals, including indexing and ranking. Experience with retrieval and ranking algorithms and building big data pipelines using Hadoop, Java, Scala, Spark and more. 
 
Industrial experience in search, classification, recommendation systems, or related fields. 
 
Familiarity with A/B testing and data-driven product development. 
 
Passionate about creating products loved by customers at Apple. 
 
Bachelor&rsquo;s degree or higher (or equivalent practical experience) in Computer Science, Machine Learning, Natural Language Processing, Artificial Intelligence, or a related field. 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Machine Learning Engineer, ASE Search Team

OpenAI

<div>
 
 About The Team
 
 
 
 The Youth Well-Being product team is part of the Integrity pillar at OpenAI, responsible for ensuring that our state-of-the-art AI technologies are deployed in safe, age-appropriate, and beneficial ways&mdash;especially for youth and families.
 
 
 We work across OpenAI&rsquo;s entire product surface area, from ChatGPT to future-facing tools, to architect safety and trust into the foundation of our systems. Our mission: empower families while meeting the highest standards of regulatory compliance and ethical responsibility.
 
 
 This work is core to OpenAI&rsquo;s mission to ensure AGI benefits all of humanity. Safety, especially for the most vulnerable users, is more important to us than unfettered growth.
 
 
 
 About The Role
 
 
 
 We&rsquo;re looking for a Senior Software Engineer to help architect and build the foundational systems that power family- and youth-facing experiences at scale. You&rsquo;ll help define how teens and guardians engage with OpenAI products&mdash;ensuring those experiences are safe, compliant, and empowering.
 
 
 You&rsquo;ll operate across a broad technical surface: building identity primitives, age assurance pipelines, and guardian tools that support both proactive and reactive interventions. You&rsquo;ll collaborate closely with a cross-functional team of engineers, data scientists, designers, user researchers, and policy experts.
 
 
 This is a high-impact, 0&rarr;1 opportunity to set the standard for how families interact with generative AI.
 
 
 
 In This Role, You Will
 
 
 
 <ul>
 <li>
 Architect and implement teen and guardian experiences across OpenAI products, including ChatGPT.
 </li>
 <li>
 Build global age assurance systems that are privacy-preserving and tailored to regional compliance needs.
 </li>
 <li>
 Design and evolve our identity infrastructure to support scalable, secure, and resilient user journeys at consumer internet scale.
 </li>
 <li>
 Help define safety and well-being metrics, and continuously improve user trust through technical interventions.
 
 
 </li>
 </ul>
 
 You Might Thrive In This Role If You
 
 
 
 <ul>
 <li>
 Have built products or infrastructure for users under 18, or have a strong interest in digital safety, youth well-being, or educational technology.
 </li>
 <li>
 Have hands-on experience with identity platforms, auth/authz systems, or user verification at scale.
 </li>
 <li>
 Have worked on systems with regulatory complexity (e.g., COPPA, GDPR-K, UK OSA, KOSA) or experience navigating legal constraints in product development.
 </li>
 <li>
 Are comfortable owning complex, ambiguous problems end-to-end, learning quickly, and adapting to fast-changing priorities. Can thrive in a cross-functional team, with strong collaboration across policy, research, legal, and product functions.
 </li>
 <li>
 Care deeply about building systems that are not just performant, but also inclusive, thoughtful, and ethical.
 
 
 </li>
 </ul>
 
 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&rsquo;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, and requests can be made via this link.
 
 
 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 Range: $230K - $385K
 
 
</div>

Software Engineer, Youth Well-Being

Quantcast

<div><div>At Quantcast, we don't just build advertising technology, we revolutionize how it works. Our AI-powered Demand Side Platform (DSP) connects the world's most ambitious marketers with their ideal audiences across the open internet, delivering results that actually move the needle. Since 2006, we've been the industry's trailblazer, launching the first AI-powered measurement platform for publishers and the first AI-driven DSP. Our AI doesn't just optimize&mdash;it delivers the measurable outcomes that matter most to our clients, giving them the competitive edge they need in a crowded marketplace. Ready to join the team that's defining the future of digital advertising?</div><div></div><div> 
The Modeling team is responsible for Machine Learning (ML) systems at Quantcast. We build and maintain multiple ML products that price millions of bid requests per second in a real-time auction environment to maximize advertiser outcomes. For each bid our models predict age, gender, viewability, fraud, advertiser relevance and many more characteristics. Using NLP, clustering and LLMs we build topics in multiple languages to help our advertisers target customers interested in relevant content.</div>
<div></div>
<div>As a Machine Learning Engineer you care about the health and maintainability of our systems and the velocity of the engineering teams. You explore data, research new algorithms, experiment with proof of concepts, and build out scalable real-time production systems to tackle challenges the company faces.</div>
<div></div>
<h3 class="jobSectionHeader">What you'll do:</h3><ul>
<li>Design, code, test, and debug ML applications and constantly improve large-scale global systems that respond to millions of real-time requests per second efficiently.</li>
<li>Run Machine Learning experiments to test new modeling ideas.</li>
<li>Write clean, efficient, and maintainable code using industry best practices.</li>
<li>Collaborate closely with engineering teams, to deliver high-quality ML products. Participate in code reviews and provide constructive feedback to team members.</li>
<li>Identify performance bottlenecks and optimize system components for enhanced scalability.</li>
<li>Keep up to date with developments in machine learning outside the company.</li>
</ul><h3 class="jobSectionHeader">Who you are:</h3><ul>
<li>New Grad to 1 year of experience.</li>
<li>You must be work-authorized in the United States without the need for employer sponsorship.</li>
<li>This is a hybrid role based in our San Francisco office. To ensure a manageable commute for in-office days, candidates must reside within a 60-mile radius of San Francisco, CA. No relocation candidates at this time.</li>
<li>Fluency in Python, Java or similar programming languages.</li>
<li>Strong skills in mathematics and statistics.</li>
<li>Working knowledge of ML algorithms such as classification, control systems, optimization, clustering, LLMs or recommendation systems.</li>
<li>An interest in distributed system and software design, concurrent algorithms, data structures, and software engineering.</li>
</ul><div>The expected base salary range for this role is $151,300 to $178,000.</div><div></div><div> 
At Quantcast, we craft offers that reflect your unique skills, expertise, and geographic location. On top of a competitive salary, this position includes a performance bonus, equity, and a comprehensive benefits package. For more details, visit our Careers Page and see how we support our team. We are headquartered in San Francisco with offices around the world. Quantcast is an Equal Opportunity Employer. Please see the Applicant Privacy Notice for details on our applicant privacy policy. Join the team that unlocks potential.</div></div><div></div>

Machine Learning Engineer

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)

David Joseph & Company

<div><h2 class="jobSectionHeader">Founding Engineer &mdash; Confidential (AI Startup, YC/a16z-Backed)</h2>
Location: San Francisco, CA (Onsite, 5 days/week) 
Compensation: $180,000 &ndash; $225,000 base + 1.0% &ndash; 1.5% equity 
Visa Sponsorship: Available &mdash; visa transfers supported | Relocation support available 
Employment Type: Full-Time<h3 class="jobSectionHeader">
About the Company</h3>
A well-funded AI startup building a new paradigm for software creation &mdash; using AI agents to autonomously create and operate specialized software products at scale. Founded in 2026, the company has raised $5.5M from a16z and other top-tier investors and is building out its founding engineering team of 5&ndash;7 engineers. The founding team has previously scaled companies to $20M ARR.<h3 class="jobSectionHeader">
The Role</h3>
This is a founding engineering role for a generalist full-stack engineer who loves building from zero. You will ship micro apps weekly to real users, encode your processes into increasingly automated workflows, and run rapid experiments with the founding team. All engineers report directly to the founder and CEO.<h3 class="jobSectionHeader">
What You'll Own</h3><ul><li>
Build and ship micro apps every week with real users, encoding your processes into increasingly automated workflows</li><li>
Work in close collaboration with the founding team</li><li>
Run rapid experiments and decisively double down on what works while cutting what doesn't</li></ul>
Tech stack: Full-stack, AI &mdash; Python, JavaScript, Kotlin, Go (flexible on language)<h3 class="jobSectionHeader">
Requirements</h3><ul><li>
1&ndash;5 years of software engineering experience building AI-driven products</li><li>
Experience shipping products or features from ideation to real users with significant traction</li><li>
Proficiency in agentic development &mdash; designing and building orchestration pipelines across multiple agents, tools, and services</li><li>
Full-stack proficiency with a backend focus</li><li>
Active user of modern AI tooling (e.g. Claude Code, Cursor, or similar)</li><li>
At least one clear signal of excellence &mdash; hackathon wins, side projects with significant traction, impressive fellowships, YC founder background, etc.</li><li>
Bachelor's degree in Computer Science or a related technical field</li><li>
Must be based in or willing to relocate to San Francisco</li></ul><h3 class="jobSectionHeader">
Preferred</h3><ul><li>
Previous founder or early-stage startup experience &mdash; YC or a16z alum backgrounds a strong plus</li><li>
Degree from a top-tier university (Berkeley, Stanford, CMU, or equivalent)</li></ul><h3 class="jobSectionHeader">
This Role Is NOT For</h3><ul><li>
Pretraining or fine-tuning ML researchers &mdash; this is applied agentic engineering, not model training</li><li>
Pure Big Tech careers with no side project, startup, or scrappy chapter</li><li>
Candidates with a pattern of short tenures across multiple companies</li></ul><h3 class="jobSectionHeader">
Interview Process</h3><ul><li>
Application review</li><li>
Intro screen (45 min) &mdash; technical depth, past projects, judgment, and founder fit</li><li>
Pair coding session (60 min) &mdash; live coding, no AI tools; CS fundamentals and algorithmic reasoning</li><li>
Onsite (~4 hours) &mdash; agentic coding session, system design, and behavioral/founder-fit conversation</li><li>
Offer</li></ul><h3 class="jobSectionHeader">
Logistics</h3><ul><li>
Role is fully onsite in San Francisco (SoMa) &mdash; 5 days/week</li><li>
Relocation support available</li><li>
Visa sponsorship available</li></ul>
Shortlisted candidates will be contacted by David Joseph &amp; Co., the recruiting partner managing this search.</div>

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