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Prolific

<div>
 
 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&rsquo;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&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 participant, where you&rsquo;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&rsquo;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&rsquo;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)

Handshake

<div><h1 class="jobSectionHeader">About Handshake</h1>
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><h1 class="jobSectionHeader">
About the Role
</h1>Handshake is hiring an Associate Machine Learning Engineer for the Growth Relevance team. AI is transforming how students navigate their careers, and we're committed to providing innovative, responsible AI-powered solutions that guide students from educational aspirations to meaningful career opportunities. In this role, you will contribute directly to this mission by developing, deploying, and enhancing machine learning systems focused on lifecycle optimization, personalized notifications, and monetization strategies.
You'll join a high-impact team leveraging cutting-edge ML infrastructure, including embedding-based retrieval, Graph Neural Networks, and multi-stage rankers built upon a robust data platform with billions of data points. Your work will drive critical marketplace metrics, enhance user engagement, and contribute to responsible AI practices around explainability, fairness, and quality.
What You'll Do<ul><li>
Innovator: Develop and iterate on machine learning models and features that directly influence user experience across lifecycle, notifications, and monetization &mdash; with guidance from senior engineers.</li><li>
Collaborator: Partner with senior engineers, data scientists, and product managers to develop and iterate on machine learning models that improve product features and user experience.</li><li>
Learner: Grow your technical depth by working alongside experienced ML practitioners, picking up best practices in model development, experimentation, and production deployment.</li></ul><h1 class="jobSectionHeader">
Desired Capabilities
</h1><ul><li>Bachelor&rsquo;s degree in Computer Science, Data Science, or a related field</li><li>
0&ndash;2 years of experience in machine learning, data science, or a related area</li><li>
Proficient in Python, with hands-on experience in frameworks such as scikit-learn, PyTorch, or TensorFlow</li><li>
Strong foundation in core ML concepts, including classification, regression, ranking, and model evaluation</li></ul>
Extra Credit<ul><li>
Master&rsquo;s degree or currently pursuing an advanced degree in a relevant field</li><li>
Exposure to areas such as recommendations, personalization, NLP, deep learning, LLMs, or explainable AI</li><li>
Familiarity with the ML lifecycle (e.g., experiment tracking, model monitoring, feature pipelines)</li><li>
Experience with cloud platforms (GCP, AWS, or Azure)</li><li>
Clear communicator, able to translate technical work for diverse audiences</li><li>
Collaborative mindset with experience working cross-functionally with product, analytics, and engineering teams</li></ul><h1 class="jobSectionHeader">
Perks</h1>
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
Connection: Team outings &amp; referral bonuses
Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.
Compensation Range: $115K - $144K</div>

Associate Machine Learning Engineer

Genentech

<div><div><div>THE POSITION</div>
Job Summary
The Senior Data Scientist in Data, Analytics, and AI develops, deploys, and industrializes enterprise applications leveraging machine learning techniques to extract value from structured and unstructured data across Commercial and Medical domains. Acting as a strategic thought partner, the role involves shaping impactful business priorities, collaborating cross-functionally, and delivering actionable insights. The position requires a strong execution mindset, commitment to data quality and governance, and the ability to communicate complex findings to different audiences&mdash;all while staying at the forefront of AI innovation and aligning with Genentech&rsquo;s standards and compliance.
Key Job Responsibilities<ul><li>
Drive the development, deployment, and industrialization of enterprise applications using machine learning techniques (e.g., classification, regression, and forecasting) to generate value from structured and unstructured data for Commercial and Medical organizations.</li><li>
Develop a deep understanding of customers and market dynamics, and apply your technical skills to advance that knowledge and guide the organization, delivering products that help create an integrated customer experience for customers.</li><li>
Help stakeholders define clear, impactful business priorities, and where possible, use their own expertise or existing analysis/research to influence and guide.</li><li>
Act as subject matter expert for applicable Data Science and other advanced analytical methodologies, programs, and projects. Collaborate within cross‑functional teams to develop efficient Machine Learning‑based applications, gain alignment and deliver impactful business insights; engage necessary stakeholders to enable better decision‑making.</li><li>
Take an enterprise mindset, linking individual responsibilities with broader organization; focus on outcomes that provide most business value.</li><li>
Apply data science and other advanced analytical methodologies, using multiple data sources and tools.</li><li>
Collaborate with data science product owners/managers, data leads, ML Engineers, and MLOps team to develop efficient machine learning-based applications, gain alignment, and deliver impactful business insights.</li><li>
Communicate findings effectively to both technical and non-technical audiences.</li></ul> 
Who You Are<ul><li>
Bachelor's degree in Statistics, Mathematics, Computer Science, or a related quantitative field.</li><li>
5 years of experience in data science or related roles.</li><li>
Proficiency in programming languages such as Python, R.</li><li>
Knowledge of SQL for database management.</li><li>
Strong expertise in Machine Learning and Deep Learning techniques</li><li>
Excellent verbal and written communication skills, with the ability to present complex data analyses to non-technical stakeholders.</li><li>
Strong critical thinking and problem-solving abilities, with a detail-oriented approach to data analysis.</li></ul> 
Preferred Qualifications<ul><li>
Experience working with large and complex data sets in collaboration with business and analytics teams.</li><li>
Experience with deep learning frameworks (e.g., TensorFlow, PyTorch).</li><li>
Contributions to open source projects or publications in data science.</li><li>
Experience in healthcare, pharmaceutical, or highly regulated industries.</li><li>
Relevant certifications in data science, machine learning, or AI technologies (e.g., Certified Analytics Professional, AWS or similar certifications).</li><li>
Experience working with large, complex data using Hadoop or Spark or any other big data platforms.</li><li>
Proficiency with industry-standard programming languages such as Python.</li><li>
Experience with other Data Science and cloud-computing tools and platforms (AWS, GCP, etc.).</li><li>
Proficiency using ML in a variety of contexts such as insight generation, ROI calculation, text classification, clustering etc.</li><li>
Experience with data visualization tools such as tableau, and/or Qlik, and/or data studio etc.</li><li>
Experience translating research or analysis to communicate (in presentations and in writing) concise and compelling business stories that influence decisions and strategy.</li></ul>
Location<ul><li>
This position is based in South San Francisco, CA at our Genentech Campus</li><li>
Relocation benefits are NOT available for this posting</li></ul>
The expected salary range for this position based on the primary location of South San Francisco, CA is $185,200/yr to $343,900/yr. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
 Benefits
#LI-CM4
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.</div>
<div><div>JOB FACTS
</div><div><div><ul><div>Job Sub Category
Computational Biology
</div><div>Schedule
Full time
</div><div>Job Type
Regular
</div><div>Posted Date
Apr 2nd 2026
</div><div>Job ID
202604-108637</div></ul></div></div></div></div>

Senior Data Scientist

Baseten

<div>
 
 About Baseten
 
 
 
 Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $300M Series E, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. Join us and help build the platform engineers turn to to ship AI products.
 
 
 
 THE ROLE
 
 
 
 This role sits at the applied end of our post-training research efforts. You will work directly with stakeholders from the world&rsquo;s fastest-growing AI companies to post-train open-source models that outperform frontier closed models on their specialised tasks. Your day-to-day is finding creative ways to extract signal from complex, domain-specific datasets and building the reward functions, environments, eval harnesses, and training pipelines that turn that signal into better models. The models you train ship to production and reach millions of users.
 
 
 We are looking for people with hands-on LLM fine-tuning and RL experience. Researchers who are excited by the prospect of shipping models into production, who can translate a customer's domain-specific requirements into an effective training curriculum, and who know when to be rigorous and when to iterate fast.
 
 
 
 RECENT RESEARCH
 
 
 
 <ul>
 <li>
 Dense, on-policy or both?
 </li>
 <li>
 Repeated kv cache for long-running agents
 </li>
 <li>
 Distillation without the dark &ndash; replicating black-box on-policy distillation on Baseten
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design and run post-training pipelines: SFT, GRPO, DPO, RLVR, reward function engineering, and synthetic data generation.
 </li>
 <li>
 Build task-specific training environments and evals tailored to customer domains like healthcare, code generation, and legal, spanning multi-turn tool use, sandboxed execution, and agentic workflows.
 </li>
 <li>
 Work directly with customers to translate production data into training signal, designing reward loops from real usage patterns and handling distribution shift.
 </li>
 <li>
 Run and analyze training experiments end-to-end: diagnose reward hacking, importance sampling drift, and advantage estimation instabilities.
 </li>
 <li>
 Publish findings at top venues and contribute to Baseten's open-source training libraries.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Hands-on experience training LLMs with reinforcement learning &mdash; demonstrated understanding of GRPO or PPO beyond recipe-level reproduction, including group advantage computation, clipped objectives, and KL penalty design
 </li>
 <li>
 Strong intuition for reward engineering: the ability to distinguish between a reward that trains effectively and one that will exploit at scale
 </li>
 <li>
 Experience building multi-turn agent environments with tool use, not limited to single-turn question-answering setups
 </li>
 <li>
 Comfort working across the full pipeline from dataset construction through training, evaluation, and deployment
 </li>
 <li>
 Experience with production ML systems. Preference for candidates who have closed a training&ndash;inference loop where production data feeds back into model improvement
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with RL training frameworks
 </li>
 <li>
 Publications at NeurIPS, ICML, ICLR, focused on RL for LLMs, reward modeling, or alignment
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Competitive compensation, including meaningful equity.
 </li>
 <li>
 100% coverage of medical, dental, and vision insurance for employee and dependents
 </li>
 <li>
 Generous PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
 </li>
 <li>
 Paid parental leave
 </li>
 <li>
 Company-facilitated 401(k)
 </li>
 <li>
 Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
 
 
 </li>
 </ul>
 
 Apply now
 
 to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
 
 
 
 At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
 
 
 
 
 We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
 
 
 
 Compensation Range: $200K - $275K
 
 
</div>

Post-Training Applied Researcher

Loop

<div>
 
 About Loop
 
 
 
 Loop is on a mission to unlock profits trapped in the supply chain (https://loop.com/article/unlock-profit-trapped-in-your-supply-chain) and lower costs for consumers. Bad data and inefficient workflows create friction that limits working capital and raises costs for every supply chain stakeholder.
 
 
 Loop&rsquo;s modern audit and pay platform uses our domain-driven AI to harness the complexity of supply chain data and documentation. We improve transportation spend visibility so companies can control their costs and power profit. That is why industry leaders like J.P. Morgan Chase, Great Dane, Emerge, and Loadsmart work with Loop.
 
 
 Our investors include J.P. Morgan, Index Ventures, Founders Fund, 8VC, Susa Ventures, Flexport, and 50 industry-leading angel investors. Our team brings subject matter expertise from companies like Uber, Google, Flexport, Meta, Samsara, Intuit, Rakuten, and long-standing industry leaders like C.H. Robinson.
 
 
 
 About The Role
 
 
 
 Loop is growing its AI team and you&rsquo;ll have the opportunity to build both AI models and features that directly impact Loop&rsquo;s business. Loop is positioned to disrupt the incumbent freight audit and pay market, and is one of the companies leading the AI services wave, utilizing AI to automate complex back-office workflows and tasks. You will face and solve many complex technical challenges while you receive guidance and feedback from the team. The range of work here is broad, you can work on everything from training and deploying in-house multimodal LLMs, scaling our inference infrastructure, or building out and shipping agentic workflows. In doing so, you&rsquo;ll have the opportunity to define how the AI and broader Loop team will grow.
 
 
 
 What you will work on
 
 
 
 Our primary focus has been on document extraction and understanding, where we utilize multimodal LLMs, including our own in-house foundation model, to extract, normalize, and link data together into our domain model. As Loop&rsquo;s customers rely on Loop to ingest and normalize highly accurate data, we hold ourselves to a high standard to build models with a very high level of accuracy. In tandem, Loop&rsquo;s machine learning platform requires a high degree of reliability and scalability, and we expect our training and inference volume to scale several orders of magnitude in the coming year. Going forward, Loop will expand its AI capabilities, expanding into other areas such as workflow automation and audit, where we will utilize agents to tackle these problems.
 
 
 This role spans multiple domains:
 
 
 <ul>
 <li>
 ML modeling &ndash; training, evaluating, and deploying models.
 </li>
 <li>
 AI engineering &ndash; utilizing and orchestrating API LLM models to build agents to solve business problems at Loop.
 </li>
 <li>
 Backend engineering &ndash; building out frameworks to enable AI agents at scale.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 1+ years of hands-on experience in deep learning frameworks (e.g., PyTorch, Tensorflow, etc.) or shipping agents to production.
 </li>
 <li>
 Solid understanding of fundamental ML algorithms, especially multimodal LLMs.
 </li>
 <li>
 Experience fine-tuning LLMs and deploying them to production or building out agentic systems.
 </li>
 <li>
 Ability to ship high-quality code to production.
 </li>
 <li>
 Experience in cloud environments (AWS, Google, Azure).
 </li>
 <li>
 Strong communication skills and willingness to collaborate in a cross-functional team environment with domain experts.
 </li>
 <li>
 Keep up to date with the latest AI research.
 </li>
 <li>
 Ability to work in a fast-paced environment.
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 <ul>
 <li>
 Base pay 130k - 200k
 
 
 </li>
 </ul>
 
 Benefits &amp; Perks
 
 
 
 <ul>
 <li>
 Premium Medical, Dental, and Vision Insurance plans
 </li>
 <li>
 Insurance premiums covered 100% for you
 </li>
 <li>
 Unlimited PTO
 </li>
 <li>
 Fireside chats with industry leading keynote speakers
 </li>
 <li>
 Off-sites in locales such as Napa and Tahoe
 </li>
 <li>
 Generous professional development budget to feed your curiosity
 </li>
 <li>
 Physical and Mental fitness subsidies for yoga, meditation, gym, or ski memberships
 </li>
 </ul>
</div>

AI Engineer

<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
 
 
 
 As a Software Engineer, you will play a critical role in building the products and systems that power Handshake&rsquo;s core user experiences&mdash;from search and discovery to onboarding and beyond. You&rsquo;ll work across the full stack, shipping features that directly impact how millions of users find opportunities, connect with employers, and launch their careers.
 
 
 You&rsquo;ll collaborate closely with product managers, designers, and other engineers to deliver polished, end-to-end experiences in a fast-paced, mission-driven environment. Whether you&rsquo;re building AI-powered features, scaling backend systems, or crafting intuitive frontends, your work will have real, measurable impact on users at scale.
 
 
 
 Location: San Francisco, CA | 5 days/week in-office
 
 
 
 <ul>
 <li>
 Design and implement scalable full-stack systems powering core user journeys, including search, discovery, matching, and onboarding flows.
 </li>
 <li>
 Build and iterate on product features across frontend and backend surfaces, balancing speed with code quality and correctness.
 </li>
 <li>
 Ship backend APIs, asynchronous workflows, and frontend experiences that are reliable, scalable, and intuitive.
 </li>
 <li>
 Partner closely with product managers and designers to translate requirements into polished, end-to-end user experiences.
 </li>
 <li>
 Write high-quality, maintainable code while contributing to code reviews and engineering best practices.
 </li>
 <li>
 Debug and resolve issues related to system reliability, user flows, and performance.
 </li>
 <li>
 Contribute to architectural decisions and help establish patterns for scalable, secure deployments.
 </li>
 <li>
 Grow toward increased technical ownership by learning from senior engineers on the team.
 
 
 </li>
 </ul>
 
 Desired Capabilities
 
 
 
 <ul>
 <li>
 2+ years of professional software engineering experience building full-stack applications.
 </li>
 <li>
 Strong proficiency in TypeScript, with comfort working across frontend and backend.
 </li>
 <li>
 Experience with modern web stacks (e.g., React, Next.js, GraphQL, Ruby on Rails).
 </li>
 <li>
 Solid understanding of relational databases (e.g., PostgreSQL) and data modeling.
 </li>
 <li>
 Product-oriented mindset with a focus on user experience and business outcomes.
 </li>
 <li>
 Strong communication skills and comfort collaborating cross-functionally with product, design, and other engineering teams.
 </li>
 <li>
 Comfortable working in a fast-paced, dynamic environment with a focus on continuous learning and improvement.
 
 
 </li>
 </ul>
 
 Extra Credit
 
 
 
 <ul>
 <li>
 Experience with AI-powered products, chatbots, conversational interfaces, or agentic frameworks (e.g., OpenAI APIs).
 </li>
 <li>
 Familiarity with workflow orchestration tools such as Temporal or asynchronous job systems.
 </li>
 <li>
 Exposure to matching systems, marketplaces, or multi-step onboarding flows.
 </li>
 <li>
 Experience with cloud infrastructure (AWS, GCP) and deployment pipelines.
 </li>
 <li>
 Background at high-growth or scaling technology companies.
 </li>
 <li>
 Familiarity with component libraries, design systems, and building reusable interfaces for rapid deployment.
 
 
 </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
 
 
 🤝
 
 Connection:
 
 Team outings &amp; referral bonuses
 
 
 Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.
 
 
 Compensation Range: $145K - $170K
 
 
</div>

Software Engineer

HappyRobot

<div>
 
 About HappyRobot
 
 
 
 HappyRobot is the infrastructure for enterprises to build and orchestrate AI workforces. Our AI workers don't just communicate - they make decisions, take action, and run operations autonomously across voice, email, and enterprise systems. Born in Y Combinator (S23) and backed by a16z and Base10 with over $60M raised, we power critical operations for global enterprises worldwide.
 
 
 Our platform is battle-tested in the most demanding environments - where AI has real consequences. We started in logistics, built our own voice stack, models, and orchestration layer from the ground up, and are now bringing that infrastructure to every enterprise that runs the real economy. Learn more about our vision in our manifesto.
 
 
 
 About The Role
 
 
 
 <ul>
 <li>
 Build foundational data products, dashboards and tools to enable self-serve analytics to scale across the company.
 </li>
 <li>
 Develop insightful and reliable dashboards to track performance of core metrics that will deliver insights to the whole company.
 </li>
 <li>
 Build and maintain robust data pipelines and models to ensure data quality.
 </li>
 <li>
 Partner with Product, Engineering, and Design teams to inform decisions.
 </li>
 <li>
 Translate complex data into clear, actionable insights for product teams.
 </li>
 <li>
 Love working with data. Love making product better. Love finding the story behind the numbers.
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Define, build, and maintain product metrics, dashboards, and pipelines.
 </li>
 <li>
 Write SQL and Python code to extract, transform, and analyze data.
 </li>
 <li>
 Design and run experiments (A/B tests) to support product development.
 </li>
 <li>
 Proactively explore data to identify product opportunities and insights.
 </li>
 <li>
 Collaborate with cross-functional teams to ensure data-driven decisions.
 </li>
 <li>
 Ensure data quality, reliability, and documentation across analytics efforts.
 
 
 </li>
 </ul>
 
 Must Have
 
 
 
 <ul>
 <li>
 3+ years of experience as an Analytics Data Engineer or similar Data Science &amp; Analytics roles.
 </li>
 <li>
 Strong SQL and data engineering skills to transform data into accurate, clean data models (e.g., dbt, Airflow, data warehouses).
 </li>
 <li>
 Proficiency in Python for data analysis and modeling.
 </li>
 <li>
 Excellent communication skills: able to explain complex data insights clearly.
 </li>
 <li>
 Curious, collaborative, and driven to make an impact in a fast-paced environment.
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Experience in B2B SaaS or AI/ML products.
 </li>
 <li>
 Familiarity with product analytics tools (e.g., Mixpanel, Amplitude).
 </li>
 <li>
 Exposure to machine learning concepts or AI-powered systems.
 
 
 </li>
 </ul>
 
 Why join us?
 
 
 
 <ul>
 <li>
 Opportunity to work at a high-growth AI startup, backed by top investors.
 </li>
 <li>
 Rapidly growing and backed by top investors including a16z, Y Combinator, and Base10.
 </li>
 <li>
 Ownership &amp; Autonomy - Take full ownership of projects and ship fast.
 </li>
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 Top-Tier Compensation - Competitive salary + equity in a high-growth startup.
 </li>
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 Comprehensive Benefits - Healthcare, dental, vision coverage.
 </li>
 <li>
 Work With the Best - Join a world-class team of engineers and builders.
 
 
 </li>
 </ul>
 
 Our Operating Principles
 
 
 
 
 
 Extreme Ownership
 
 
 
 
 We take full responsibility for our work, outcomes, and team success. No excuses, no blame-shifting &mdash; if something needs fixing, we own it and make it better. This means stepping up, even when it&rsquo;s not &ldquo;your job.&rdquo; If a ball is dropped, we pick it up. If a customer is unhappy, we fix it. If a process is broken, we redesign it. We don&rsquo;t wait for someone else to solve it &mdash; we lead with accountability and expect the same from those around us.
 
 
 
 
 Craftsmanship
 
 
 
 
 Putting care and intention into every task, striving for excellence, and taking deep ownership of the quality and outcome of your work. Craftsmanship means never settling for &ldquo;just fine.&rdquo; We sweat the details because details compound. Whether it&rsquo;s a product feature, an internal doc, or a sales call &mdash; we treat it as a reflection of our standards. We aim to deliver jaw-dropping customer experiences by being curious, meticulous, and proud of what we build &mdash; even when nobody&rsquo;s watching.
 
 
 
 
 We are &ldquo;majos&rdquo;
 
 
 
 
 Be friendly &amp; have fun with your coworkers. Always be genuine &amp; honest, but kind. &ldquo;Majo&rdquo; is our way of saying: be a good human. Be approachable, helpful, and warm. We&rsquo;re building something ambitious, and it&rsquo;s easier (and more fun) when we enjoy the ride together. We give feedback with kindness, challenge each other with respect, and celebrate wins together without ego.
 
 
 
 
 Urgency with Focus
 
 
 
 
 Create the highest impact in the shortest amount of time. Move fast, but in the right direction. We operate with speed because time is our most limited resource. But speed without focus is chaos. We prioritize ruthlessly, act decisively, and stay aligned. We aim for high leverage: the biggest results from the simplest, smartest actions. We&rsquo;re running a high-speed marathon &mdash; not a sprint with no strategy.
 
 
 
 
 Talent Density and Meritocracy
 
 
 
 
 Hire only people who can raise the average; &lsquo;exceptional performance is the passing grade.&rsquo; Ability trumps seniority. We believe the best teams are built on talent density &mdash; every hire should raise the bar. We reward contribution, not titles or tenure. We give ownership to those who earn it, and we all hold each other to a high standard. A-players want to work with other A-players &mdash; that&rsquo;s how we win.
 
 
 
 
 First-Principles Thinking
 
 
 
 
 Strip a problem to physics-level facts, ignore industry dogma, rebuild the solution from scratch. We don&rsquo;t copy-paste solutions. We go back to basics, ask why things are the way they are, and rebuild from the ground up if needed. This mindset pushes us to innovate, challenge stale assumptions, and move faster than incumbents. It&rsquo;s how we build what others think is impossible.
 
 
 
 The personal data provided in your application and during the selection process will be processed by Happyrobot, Inc., acting as Data Controller.
 
 
 
 
 By sending us your CV, you consent to the processing of your personal data for the purpose of evaluating and selecting you as a candidate for the position. Your personal data will be treated confidentially and will only be used for the recruitment process of the selected job offer.
 
 
 
 
 In relation to the period of conservation of your personal data, these will be eliminated after three months of inactivity in compliance with the GDPR and legislation on the protection of personal data.
 
 
 
 
 If you wish to exercise your rights of access, rectification, deletion, portability or opposition in relation to your personal data, you can do so through security@happyrobot.ai subject to the GDPR.
 
 
 
 
 For more information, visit
 
 
 https://www.happyrobot.ai/privacy-policy
 
 
 
 
 By submitting your request, you confirm that you have read and understood this clause and that you agree to the processing of your personal data as described.
 
</div>

Data Engineer

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