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Mercor

<div>
 
 About Mercor
 
 
 
 Mercor is at the intersection of labor markets and AI research. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development.
 
 
 Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.
 
 
 Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You&rsquo;ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society.
 
 
 Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our new San Francisco headquarters.
 
 
 
 About The Role
 
 
 
 As a Machine Learning Engineer at Mercor, you&rsquo;ll operate at the intersection of backend engineering and applied machine learning. ML Engineers at Mercor are generalists first, shipping production systems that power performance prediction, search, recommendation, and fraud detection while also bringing statistical and modeling rigor where it matters. The work spans everything from building APIs and infrastructure to training and deploying models, always tied closely to core product outcomes. You&rsquo;ll collaborate with product engineers and operations to deliver systems that directly impact how companies source talent and how candidates find opportunities
 
 
 
 You Will
 
 
 
 <ul>
 <li>
 Research, train, and productionize ML models for engagement prediction, scoring, search
 </li>
 <li>
 Build backend infrastructure and APIs to serve ML models reliably at scale.
 </li>
 <li>
 Run experiments, analyze results, and iterate quickly to improve both models and product performance.
 </li>
 <li>
 Work cross-functionally with Operations and Product to translate business needs into model-driven solutions.
 </li>
 <li>
 Wear many hats: from backend engineer to applied ML practitioner to product problem-solver.
 
 
 </li>
 </ul>
 
 What We&rsquo;re Looking For
 
 
 
 <ul>
 <li>
 Strong backend engineering skills (ex. Python/Django or similar) plus a solid foundation in applied ML and statistics.
 </li>
 <li>
 Proven experience shipping production systems or ML-driven products end-to-end.
 </li>
 <li>
 High ownership and comfort operating in ambiguous, fast-changing environments.
 </li>
 <li>
 Generalist mindset: willing to flex between backend, modeling, data pipelines, and product problem-solving.
 
 
 </li>
 </ul>
 
 Why Mercor
 
 
 
 <ul>
 <li>
 Impact: Your work powers how the world&rsquo;s leading AI labs train and test their models.
 </li>
 <li>
 Learning: Get early insights into frontier model capabilities months before the market.
 </li>
 <li>
 Growth: Work on both infrastructure and research-adjacent projects with fast paths to ownership.
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Generous equity grant vested over 4 years
 </li>
 <li>
 A $20K relocation bonus (if moving to the Bay Area)
 </li>
 <li>
 A $10K housing bonus (if you live within 0.5 miles of our office)
 </li>
 <li>
 A $1K monthly stipend for meals
 </li>
 <li>
 Free Equinox membership
 </li>
 <li>
 Health insurance
 
 
 </li>
 </ul>
 Compensation Range: $130K - $500K
 
 
</div>

Machine Learning Engineer

Together AI

<div>
 
 About The Role
 
 
 
 Together AI is seeking a Machine Learning Engineer to join our Inference Engine team, focusing on optimizing and enhancing the performance of our AI inference systems. This role involves working with state-of-the-art large language models models and ensuring they run efficiently and effectively at scale. If you are passionate about AI inference, PyTorch, and developing high-performance systems, we want to hear from you. This position offers the chance to collaborate closely with AI researchers and engineers to create cutting-edge AI solutions. Join us in shaping the future at Together AI!
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design and build the production systems that power the Together AI inference engine, enabling reliability and performance at scale.
 </li>
 <li>
 Develop and optimize runtime inference services for large-scale AI applications.
 </li>
 <li>
 Collaborate with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world.
 </li>
 <li>
 Conduct design and code reviews to ensure high standards of quality.
 </li>
 <li>
 Create services, tools, and developer documentation to support the inference engine.
 </li>
 <li>
 Implement robust and fault-tolerant systems for data ingestion and processing.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 3+ years of experience writing high-performance, well-tested, production-quality code.
 </li>
 <li>
 Proficiency with Python and PyTorch.
 </li>
 <li>
 Demonstrated experience in building high performance libraries and tooling.
 </li>
 <li>
 Excellent understanding of low-level operating systems concepts including multi-threading, memory management, networking, storage, performance, and scale.
 </li>
 <li>
 Preferred: Knowledge of existing AI inference systems such as TGI, vLLM, TensorRT-LLM, Optimum
 </li>
 <li>
 Preferred: Knowledge of AI inference techniques such as speculative decoding.
 </li>
 <li>
 Preferred: Knowledge of CUDA/Triton programming.
 </li>
 <li>
 Nice to have: Knowledge of Rust, Cython and compilers.
 
 
 </li>
 </ul>
 
 About Together AI
 
 
 
 Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society. Together, we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI. Our team has been behind technological advancements such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey to build the next-generation AI infrastructure.
 
 
 
 Compensation
 
 
 
 We offer competitive compensation, startup equity, health insurance, and other competitive benefits. The US base salary range for this full-time position is $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level, and role. Individual compensation will be determined by experience, skills, and job-related knowledge.
 
 
 
 Equal Opportunity
 
 
 
 Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunities to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.
 
 
 Please see our privacy policy at https://www.together.ai/privacy
</div>

Machine Learning Engineer - Inference

Reducto

<div>
 
 About Reducto
 
 
 
 Reducto helps AI teams ingest real world enterprise data with state of the art accuracy.
 
 
 The vast majority of enterprise data &mdash; from financial statements to health records &mdash; is locked in unstructured file formats like PDFs and spreadsheets. We train vision models to read those documents the way a human would, and make it possible to build products, train models, and automate processes at scale.
 
 
 We&rsquo;ve grown incredibly quickly, growing revenue by 7x YOY, and now work with hundreds of companies ranging from leading AI teams (Harvey, Vanta, Scale), through to enterprise (FAANG, top 3 trading firm).
 
 
 We've raised over 100M from world class investors like A16z, Benchmark, and First Round Capital, and are hiring a Machine Learning Engineer to help us train and deploy the models critical to the performance of our core product.
 
 
 
 
 We Would Love To Meet You If You:
 
 
 
 
 <ul>
 <li>
 Philosophy: You are your own worst critic. You have a high bar for quality and don&rsquo;t rest until the job is done right&mdash;no settling for 90%. We want someone who ships fast, with high agency, and who doesn't just voice problems but actively jumps in to fix them.
 </li>
 <li>
 Experience: You have 2+ years of experience with training, fine tuning, and evaluating ML models used in production systems
 </li>
 <li>
 Language/Skills: You&rsquo;re exceptional at Python or similar, and are well versed with both traditional computer vision and VLMs
 </li>
 <li>
 Tools: Build your own tools as needed&mdash;like a quick Streamlit app to test hypotheses or create a dataset.
 </li>
 <li>
 Approach: A quantitative approach to building products. Ability to debug, experiment, and iterate fast. You should be comfortable getting hands-on with the full development lifecycle, from ideation to shipping to users.
 
 
 </li>
 </ul>
 
 The Core Work Will Include:
 
 
 
 <ul>
 <li>
 Training and deploying new state of the art models for parsing and interpreting unstructured data
 </li>
 <li>
 Experimenting with novel techniques to improve LLM accuracy
 </li>
 <li>
 Build data pipelines, evaluate model performance, and integrate models into the product
 </li>
 <li>
 Working directly with the founders and customers to shape the product direction and engineering strategy
 
 
 </li>
 </ul>
 
 Bonus Points If You:
 
 
 
 <ul>
 <li>
 Have prior experience founding a company or building products at early stages
 </li>
 <li>
 Are ambitious and driven, and care a lot about doing great work with great people
 </li>
 <li>
 Keep up with the latest developments in ML/AI
 
 
 </li>
 </ul>
 This is an in person role at our office in SF. We&rsquo;re an early stage company which means that the role requires working hard and moving quickly. Please only apply if that excites you.
 
 
 
 About Reducto
 
 
 
 
 Nearly 80% of enterprise data is in unstructured formats like PDFs
 
 
 
 PDFs are the status quo for enterprise knowledge in nearly every industry. Insurance claims, financial statements, invoices, and health records are all stored in a structure that&rsquo;s simply impractical for use in digital workflows. This isn&rsquo;t an inconvenience&mdash;it&rsquo;s a critical bottleneck that leads to dozens of wasted hours every week.
 
 
 
 Traditional approaches fail at reliably extracting information in complex PDFs
 
 
 
 OCR and even more sophisticated ML approaches work for simple text documents but are unreliable for anything more complex. Text from different columns are jumbled together, figures are ignored, and tables are a nightmare to get right. Overcoming this usually requires a large engineering effort dedicated to building specialized pipelines for every document type you work with.
 
 
 
 Reducto
 
 
 Breaks Document Layouts Into Subsections And Then Contextually Parses Each Depending On The Type Of Content.
 
 This Is Made Possible By a Combination Of Vision Models, LLMs, And a Suite Of Heuristics We Built Over Time. Put Simply, We Can Help You:
 
 
 <ul>
 <li>
 Accurately extract text and tables even with nonstandard layouts
 </li>
 <li>
 Automatically convert graphs to tabular data and summarize images in documents
 </li>
 <li>
 Extract important fields from complex forms with simple, natural language instructions
 </li>
 <li>
 Build powerful retrieval pipelines using Reducto&rsquo;s document metadata
 </li>
 <li>
 Intelligently chunk information using the document&rsquo;s layout data
 
 
 </li>
 </ul>
 Benefits at Reducto
 
 
 
 At Reducto, we&rsquo;re invested in the well-being and growth of our team. Here&rsquo;s what we currently offer:
 
 
 
 <ul>
 <li>
 Unlimited PTO: We believe great work requires recharging.
 </li>
 <li>
 Lunch: Receive a free lunch to eat with your teammates daily at the office
 </li>
 <li>
 Reimbursed Transportation: Provide us with your receipts and we&rsquo;ll take care of the costs
 </li>
 <li>
 Insurance: Generous health insurance covering medical, dental, and vision.
 </li>
 <li>
 Health and Wellness Budget: We provide up to $150/mo reimbursement for health and wellness spending, such as gym memberships, fitness classes, or similar.
 </li>
 <li>
 Parental Leave: Work with us to build a leave schedule that works for you and your family
 
 
 </li>
 </ul>
 Reducto is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law.
</div>

Acceler8 Talent

<div>
 
 🚨
 
 Hiring: Machine Learning Engineer (Optimization / Decision Systems)
 
 
 
 📍 San Francisco (Onsite)
 
 
 💰 Up to $250K + Equity (Dependent on experience)
 
 
 
 
 
 Most companies still manage digital advertising like it&rsquo;s 2015. Manually adjusting budgets, guessing which campaigns work, and relying on black-box metrics from ad platforms.
 
 
 We&rsquo;re working with a venture-backed startup building something very different:
 
 
 An AI-driven optimization engine that autonomously allocates advertising spend using the same quantitative rigor used in high-frequency trading and financial markets.
 
 
 Instead of humans manually managing campaigns, their system continuously decides:
 
 
 &bull; Where budget should go
 
 
 &bull; When bids should change
 
 
 &bull; Which creative is losing performance
 
 
 &bull; How to maximize return across platforms
 
 
 
 
 
 
 What You&rsquo;ll Work On:
 
 
 
 🧠 Build models for LTV prediction and budget optimization
 
 
 ⚙️ Design risk-aware algorithms that control how millions in ad spend is deployed
 
 
 🔌 Build real-time integrations with platforms like Meta, Google &amp; TikTok
 
 
 📊 Develop simulation &amp; backtesting systems before strategies go live
 
 
 🚀 Take models from research &rarr; production &rarr; monitoring
 
 
 
 
 
 
 Ideal Background:
 
 
 
 ✔️ 4+ years in Machine Learning or Applied ML Engineering
 
 
 ✔️ Strong foundation in statistics, probability, and optimization
 
 
 ✔️ Experience deploying ML models in production systems
 
 
 ✔️ Builders who care about real-world impact, not just research
 
 
 
 
 
 ⭐ Bonus if you&rsquo;ve worked in quant finance, algorithmic trading, or adtech
 
 
 
 
 
 
 Why This Role Is Interesting:
 
 
 
 &bull; You&rsquo;ll build systems that control real-world financial decisions
 
 
 &bull; Early engineer helping shape the core architecture
 
 
 &bull; Opportunity to work on a $1T+ global market
 
 
 &bull; Meaningful equity at an early stage
 
 
 
 
 
 If you're interested or know someone who might be, DM me or apply below 👇👇
 
</div>

Kickmaker

<div><div>Kickmaker is a high-tech product design and industrialization agency.</div>
<div></div>
<div>We support our customers from prototype to production run in our main vertical markets (medical, new mobility, electrification, agrotech, robotics, IOT and consumer devices) and our cross-disciplinary skills (embedded AI, high-tech manufacturing automation, eco-design, industrial design and WEB 3.0 for the economy of functionality).</div>
<div></div>
<div>We're evolving with a real maker culture! Passion, excitement and kindness are the pillars of KICKMAKER. This team and community spirit has enabled us to shape a unique corporate culture. Our approach: to enable everyone to fulfill their potential by working on exciting projects, and to encourage autonomy and initiative.</div>
<div></div>
<div>Present in France, China and the United States, our community counts over 250 passionate kickers and keeps growing. It is in this context that we are looking to strengthen our team in Boston, Seattle and San Fransisco.</div><div></div><div> 
Within Kickmaker, the employee will assume the role of AI engineer, with the following main responsibilities:

Supporting the qualification of Kickmaker clients&rsquo; requirements, as well as ensuring proper technical follow-up and management of projects for the assigned scope. As an integral part of the project team, he/she collaborates with other technical experts and contributes to the successful completion of the project within the defined timeline and budget.

General responsibilities related to the role:
<ul>
<li>Analyze sensors for data acquisition (RGB, depth, LiDAR, pressure, and others)</li>
<li>Design and implement data processing architectures</li>
<li>Perform business and technical analysis of data to understand underlying phenomena</li>
<li>Generate real and/or synthetic datasets (using Blender or other tools)</li>
<li>Implement classical algorithms</li>
<li>Apply Deep Learning approaches, including the use of pre-trained networks or training custom models</li>
<li>Test and analyze Deep Learning models</li>
<li>Review scientific publications and identify potential opportunities</li>
<li>Improve robustness and optimize Deep Learning models (e.g., deployment on microcontrollers)</li>
</ul>
More generally, the employee shall also ensure the development and maintenance of the company&rsquo;s brand image with its clients and ensure compliance with applicable procedures, both in the performance of their own duties and with regard to the employees under their supervision.

The employee must remain aware of the responsibilities associated with the performance of their duties and may not claim to have been unaware of them under any circumstances.

In carrying out the responsibilities described above, and more broadly in the performance of all activities within the Company, the employee shall be placed under the direct supervision of the Executive Management of Kickmaker.
<ul>
<li>Location: San Francisco, California, USA</li>
<li>Base Salary: $155 000 to $180 000/ year</li>
<li>Experience Required: 5 years in a relevant field</li>
</ul></div><div><div>Your adventure at Kickmaker</div>
<div></div>
<div>At Kickmaker you&rsquo;ll work on 5&ndash;10 projects annually, choosing from a wide range of industries : from robotics, medical devices, fitness tech, and automotive, to micro-mobility, beauty tech, sports exoskeletons, and AI-driven hardware.
</div><div>Your path evolves with your curiosity: we help you grow where your professional ambitions and personal passions meet, always connected to the latest tech breakthroughs.</div>
<div></div>
<div>We offer a benefits package designed to support you and your family while keeping costs low. This includes health and dental coverage, paid time off and 5 sick days for rest and renewal. You can also join our 401(k) plan to invest in your future.</div>
<div></div>
<div>Our Culture &amp; Spirit</div>
<div>Kickmaker is built by innovators, for innovators. Across our 7 offices we give you the tools to make your ideas happen.</div> 
<div></div>
<div></div><div>Our vision is simple: build a space where innovators can explore, experiment, and push boundaries together.</div>
<div>If you&rsquo;re curious about our spirit and way of working (and you&rsquo;ve got a minute) check out this short video where Leonardo da Vinci &ldquo;visits&rdquo; Kickmaker.An image is worth a thousand words, and this one will give you the full vibe</div>
<div></div>
<div>If you&rsquo;ve ever looked at a product and thought, &ldquo;I could build this better,&rdquo; let&rsquo;s talk!</div>
</div>
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</div>

AI Engineer

J&T Business Consulting

<div><div><div>Company: Confidential Client 
</div><div>Location: San Francisco, CA (Hybrid) 
</div><div>Salary: $240,000 &ndash; $380,000 base + equity + bonus 
</div><div>Recruitment Partner: J&amp;T Recruitment &ndash; Exclusively Retained 
</div>J&amp;T Recruitment has been exclusively retained by a rapidly scaling AI technology company in San Francisco that is building cutting-edge generative AI platforms used by global enterprise clients. 
They are seeking a Senior AI Engineer to design and deploy production-grade machine learning systems and contribute to the architecture of next-generation AI products.<h3 class="jobSectionHeader"> 
Key Responsibilities</h3> 
<ul><li>Design, train, and deploy large-scale machine learning and generative AI models</li> 
<li>Build scalable data pipelines for model training and inference</li> 
<li>Develop production-ready ML services and APIs</li> 
<li>Work closely with product managers and data scientists to translate research into production systems</li> 
<li>Optimize models for performance, cost, and latency</li> 
<li>Contribute to the design of distributed AI infrastructure</li> 
<li>Stay up to date with advancements in LLMs, transformer architectures, and generative AI</li> 
</ul><h3 class="jobSectionHeader">Tech Stack</h3> 
<ul><li>Python</li> 
<li>PyTorch / TensorFlow</li> 
<li>Hugging Face / Transformers</li> 
<li>Kubernetes</li> 
<li>AWS / GCP</li> 
<li>Vector databases</li> 
<li>ML pipelines (Airflow / Kubeflow)</li> 
</ul><h3 class="jobSectionHeader">Requirements</h3> 
<ul><li>5+ years of experience in Machine Learning or AI Engineering</li> 
<li>Strong experience building and deploying ML models to production</li> 
<li>Experience working with LLMs, NLP, or generative AI systems</li> 
<li>Strong programming skills in Python</li> 
<li>Experience with distributed systems and cloud platforms</li> 
</ul><h3 class="jobSectionHeader">Interview Process</h3> 
<div><ul><li>Recruiter Screening (30 minutes) &ndash; Introduction via J&amp;T Recruitment</li></ul> 
<ul><li>Technical Coding Interview (60 minutes) &ndash; Python and ML fundamentals</li></ul> 
<ul><li>Machine Learning System Design (90 minutes) &ndash; Designing scalable ML architecture</li></ul> 
<ul><li>Technical Deep Dive (90 minutes) &ndash; Discussion around previous AI projects</li></ul> 
<ul><li>Final Leadership Interview (45 minutes) &ndash; Cultural and team alignment</li></ul></div></div></div><div></div>

Senior AI Engineer

Hayden AI

<div>
 
 About Us
 
 
 
 At Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.
 
 
 From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future.
 
 
 
 Job Title:
 
 Machine Learning Operations Engineer
 
 
 
 Company:
 
 Hayden AI Technologies, Inc.
 
 
 
 Location:
 
 460 Bryant Street, Suite 100, San Francisco, CA 94107
 
 
 
 Position Duties
 
 
 
 <ul>
 <li>
 Optimize orchestration processes to ensure efficient deployment and management of AI models.
 </li>
 <li>
 Implement cost-saving strategies to minimize infrastructure expenses while maximizing performance.
 </li>
 <li>
 Upgrade throughput to enhance scalability and responsiveness of AI systems.
 </li>
 <li>
 Collaborate with cross-functional teams to identify bottlenecks and implement solutions to improve workflow efficiency.
 </li>
 <li>
 Ship new features and updates rapidly while maintaining high levels of quality and reliability.
 </li>
 <li>
 Deploy and monitor machine learning models produced by deep learning engineers.
 </li>
 <li>
 Design, deploy, and maintain performant and scalable processes for data acquisition and manipulation to enhance dataset accessibility.
 </li>
 <li>
 Participate actively in the team's software development process, including design reviews, code reviews, and brainstorming sessions.
 </li>
 <li>
 Maintain accurate and updated software development documentation.
 
 
 </li>
 </ul>
 
 Degree Requirements
 
 
 
 Bachelor of Science or Engineering degree or a foreign equivalent in Robotics, Machine Learning, Computer Science, Electrical Engineering, Electronics and Telecommunication Engineering, or a related field.
 
 
 
 Experience Requirement
 
 
 
 One (1) year of work experience in the job offered or as a Deep Learning Engineer, Perception Engineer II, MLOps, Research Engineer II, Machine Learning, Computer Vision Intern, or another related deep learning engineer role.
 
 
 
 Other Special Requirements
 
 
 
 <ul>
 <li>
 One (1) year of work experience with all of the following:
 </li>
 <ul>
 <li>
 Deploying real-world applied computer vision (including deep learning models) on edge devices
 </li>
 <li>
 Python programming and software design
 </li>
 <li>
 C++
 </li>
 <li>
 Software development tools and libraries including PyTorch, OpenCV, TensorFlow, MLflow
 </li>
 <li>
 Automated data annotation
 </li>
 <li>
 Distributed training in the cloud
 </li>
 <li>
 Deploying and managing GPU clusters for ML pipelines and workflows
 
 </li>
 </ul>
 </ul>
 
 Rate of Pay:
 
 $135,699.00 to $190,000.00 per year
 
 
 
 Location of Position and Interview:
 
 
 
 Hayden AI Technologies, Inc.
 
 
 460 Bryant Street, Suite 100
 
 
 San Francisco, CA 94107
 
 
 
 Applicants Should Submit Resumes To
 
 
 
 Janet Le-Mcintosh
 
 
 janet.le@hayden.ai
 
 
 Hayden AI Technologies, Inc.
 
 
 460 Bryant Street, Suite 100
 
 
 San Francisco, CA 94107
</div>

Machine Learning Operations Engineer

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Machine Learning Operations Engineer