learning engineer

Hellyeah AI

AI Engineer - Learn Engine: Intelligence &amp; OptimizationLocation: San Francisco HQ; ShanghaiAddress: San Francisco, CaliforniaEmployment Type: Full timeLocation Type: HybridDepartment: EngineeringCompensation: San Francisco $200K - $1M + 0.5% - 3% equityBuild the brain of an autonomous growth OS. The system you create will manage millions in ad spend and get measurably smarter with every dollar. This is the moat: every competitor has humans optimizing campaigns manually. You are building the intelligence layer that compounds. The Platform engineer creates the tools; you create the decisions. Together you build something nobody else has.Must Have- Has built recommendation, optimization, or decision systems where outputs improve future inputs.- Strong statistical reasoning and experimentation judgment under noisy real-world data.- Strong LLM orchestration or agent-system experience for reasoning over campaign context.- Can design optimization policies, scoring systems, or automated recommendation loops.- AI-first development workflow and ability to ship production systems quickly.Nice to Have- Ad-tech optimization patterns: bid management, budget allocation, ROAS optimization.- Reinforcement learning experience.- Hyperparameter optimization experience.- Model fine-tuning experience.- Experience building agent-driven automation where LLM agents take actions.- Background in growth engineering, performance marketing, or data science.- Experience with Mastra or similar agent orchestration framework.What You Will OwnOwn the intelligence and optimization layer of Learn Engine. Build recommendation engines for bid changes, budget reallocation, pause/boost decisions, and postback optimization. Turn SSOT campaign data into high-quality optimization guidance and closed-loop decision systems. Define how the system learns from outcomes and continuously improves campaign strategy over time. This role owns decision quality, optimization policy, and learning loops, not platform plumbing or simulator infrastructure.Pay: $200,000.00 - $1,000,000.00 per yearWork Location: In person

AI Engineer - Learn Engine: Intelligence & Optimization

Smvsoft LLC

Founding Engineer - Applied AI San francisco, CA (Full time)- In-Office$180k-$230k per annumNO C2CAbout the RoleHiring a world-class Applied AI Engineer to build the core systems behind their automation engine for hardware engineering.This is a deeply technical, high-impact role. You will be among the first technical hires and will own mission-critical systems end-to-end. The problems are ambiguous, the constraints are real, and the expectations are high. If you move fast from idea to production, care deeply about customer experience, and want to build foundational AI infrastructure for the world's most impactful industries, this role is for you.Key Responsibilities<ul><li>Design and implement core workflows and infrastructure for hardware engineering agents, including intelligent context management, novel indexing approaches, and post-training</li><li>Build agents and ML models that can interpret, reason over, and manipulate complex engineering design data, integrating with enterprise-grade engineering tools and systems</li><li>Work closely with customers and the engineering team to deliver AI-powered workflows that are reliable, intuitive, and trusted in production environments</li><li>Prototype rapidly, validate ideas with real users, and ship frequently</li><li>Influence engineering culture, architecture decisions, and the future of the product</li></ul>RequirementsMust-Have<ul><li>Bachelor's or higher in Computer Science, Machine Learning, or equivalent experience</li><li>Strong familiarity with LLM architectures and agent research trends</li><li>Excellent programming skills with experience using ML libraries such as PyTorch, Hugging Face, and W&amp;B</li><li>Experience building production ML or AI systems</li><li>Solid practical experience with search and information retrieval</li><li>Moves fast from idea to production, with a genuine care for customer experience</li><li>Based in or willing to relocate to San Francisco, or an exceptional remote candidate</li></ul>Nice-to-Have<ul><li>2+ years in applied machine learning, backend engineering, or AI infrastructure</li><li>Experience working with machine learning over geometric data, including CAD</li><li>Track record of high-impact contributions or published papers at top-tier AI labs or teams</li></ul>Pay: $180,000.00 - $230,000.00 per yearWork Location: In person

Founding Engineer - Applied AI

Information Technology Senior Management Forum

<div><div>Posted Date
6/29/2026
</div><div>Description
<div>Senior Lead AI Engineer(MLX, Agentic AI, Gen AI platform Services)
Overview:
At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent &mdash; along with our deep experience in machine learning &mdash; position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI &amp; ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
Team Description:
The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. 
In this role, you will:<ul><li>
Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.</li><li>
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.</li><li>
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.</li><li>
Invent and introduce state-of-the-art LLM optimization techniques to improve the performance &mdash; scalability, cost, latency, throughput &mdash; of large scale production AI systems.</li><li>
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.</li></ul>
The Ideal Candidate:<ul><li>
You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.</li><li>
Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.</li><li>
You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.</li><li>
You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.</li><li>
You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.</li></ul>
Basic Qualifications:<ul><li>
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies</li><li>
At least 6 years of experience programming with Python, Go, Scala, or Java</li></ul>
Preferred Qualifications:<ul><li>
7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)</li><li>
Experience designing, developing, integrating, delivering, and supporting complex AI systems</li><li>
Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders</li><li>
Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang</li><li>
Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost</li><li>
Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production</li><li>
Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer 

Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer 

New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer 

San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer 

San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Lead AI Engineer(MLX, Agentic AI, Gen AI platform Services)
Overview:
At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent &mdash; along with our deep experience in machine learning &mdash; position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI &amp; ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
Team Description:
The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. 
In this role, you will:<ul><li>
Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.</li><li>
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.</li><li>
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.</li><li>
Invent and introduce state-of-the-art LLM optimization techniques to improve the performance &mdash; scalability, cost, latency, throughput &mdash; of large scale production AI systems.</li><li>
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.</li></ul>
The Ideal Candidate:<ul><li>
You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.</li><li>
Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.</li><li>
You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.</li><li>
You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.</li><li>
You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.</li></ul>
Basic Qualifications:<ul><li>
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies</li><li>
At least 6 years of experience programming with Python, Go, Scala, or Java</li></ul>
Preferred Qualifications:<ul><li>
7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)</li><li>
Experience designing, developing, integrating, delivering, and supporting complex AI systems</li><li>
Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders</li><li>
Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang</li><li>
Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost</li><li>
Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production</li><li>
Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer 

Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer 

New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer 

San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer 

San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</div>
</div><div>Salary
229,900.00 - 262,400.00 Annual
</div><div></div><div><div>Type<div>
Full-time</div></div></div></div>

Senior Lead AI Engineer(MLX, Agentic AI, Gen AI platform Services)

Notion

<div>
 Who We Are
 
 
 Notion is the collaborative AI workspace where teams and agents think together. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion.
 
 
 Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn&rsquo;t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business&rsquo;s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life&rsquo;s work.
 
 
 
 About The Role
 
 
 
 As an engineer at Notion, you&rsquo;ll help shape core user experiences and accelerate how people discover value in Notion. You'll tackle meaningful challenges with increasing autonomy, crafting code that millions of users will experience. You'll take ownership of projects that matter, make critical technical decisions, and contribute your unique perspective to our product vision. Working alongside passionate experts across design, product, and data, you'll help shape the future of how people work.
 
 
 We're looking for an New Grad AI Engineer to join as a strategic partner in shaping Notion's AI vision. You'll work on cutting-edge AI-powered features, leveraging LLMs, embeddings, and other AI technologies to make Notion more intelligent and capable.
 
 
 
 Role
 
 
 
 This role may be aligned to one of multiple AI-focused teams at Notion. Depending on team match and business needs, you could work on:
 
 
 <ul>
 <li>
 AI product engineering: building model-powered features end-to-end (UX, APIs, retrieval, orchestration, quality, and reliability)
 </li>
 <li>
 Model &amp; systems engineering: improving model integration and performance (latency, cost, safety, robustness) and building the infrastructure that supports model serving and experimentation
 </li>
 <li>
 Evaluation &amp; quality (evals): creating evaluation frameworks and automated/ human-in-the-loop testing to measure and improve model and product quality
 
 
 </li>
 </ul>
 What You&rsquo;ll Achieve
 
 
 <ul>
 <li>
 Partner with your team to prototype and ship an AI-powered product improvement
 </li>
 <li>
 Own a scoped productionization project: integrate a new model/technique into an existing workflow, add monitoring + guardrails, or improve latency/cost/reliability.
 </li>
 <li>
 Contribute to evals and iteration loops: build or extend an evaluation set, run experiments, analyze results, and translate learnings into product or system changes.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Pursuing a bachelor's or master&rsquo;s degree in computer science, engineering, or another related field. Must be able to start full time prior to July 27, 2026.
 </li>
 <li>
 Previous internship experience.
 </li>
 <li>
 Working towards a proficiency of one or more programming languages such as Typescript, React, Python, etc.
 
 
 </li>
 </ul>
 Skills You'll Need To Bring
 
 
 <ul>
 <li>
 Expertise building and prototyping: You&rsquo;re excited to build and iterate quickly, and you&rsquo;ve started exploring AI/ML through coursework, projects, internships, or hackathons. You&rsquo;re comfortable learning how different parts of a product fit together (UI, APIs, data), have some familiarity with relational databases like Postgres or MySQL, and can take an idea from prototype to a working feature with guidance.
 </li>
 <li>
 Problem-solving: You&rsquo;re curious and methodical. You ask good questions, break down ambiguous problems into smaller pieces, and iterate with feedback from teammates. You think about how what you build will impact users and the business.
 </li>
 <li>
 Communication and collaboration: You communicate clearly in writing and in meetings, and you&rsquo;re comfortable learning in public&mdash;sharing early work, asking for help, and incorporating feedback. You enjoy partnering with engineers and cross-functional teammates (product, design, data).
 </li>
 <li>
 Impact and user focus: You care about building the right thing, not just building it quickly. You prioritize work based on user needs and outcomes, and you&rsquo;re mindful that features at Notion can reach millions of people.
 
 
 </li>
 </ul>
 Nice To Haves
 
 
 <ul>
 <li>
 You have experience with any part of our technology stack: React, TypeScript, Node.js, Postgres, etc.
 </li>
 <li>
 You&rsquo;re a builder who finds joy in building software solutions for yourself or others
 </li>
 <li>
 You care about the interaction between technology and society, the ways in which they inform each other, and our responsibility as technologists to be conscious of that relationship.
 </li>
 <li>
 You've heard of computing pioneers like Ada Lovelace, Douglas Engelbart, Alan Kay, and others&mdash;and understand why we're big fans of their work.
 
 
 </li>
 </ul>
 Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role&rsquo;s scope and complexity, and the candidate&rsquo;s experience and expertise, and may vary from the range provided below. For roles based in San Francisco and New York, the estimated base salary range for this role is $126,000-$146,000.
 
 
 By clicking &ldquo;Submit Application&rdquo;, I understand and agree that Notion and its affiliates and subsidiaries will collect and process my information in accordance with Notion&rsquo;s Global Recruiting Privacy Policy.
 
 
 A Note on AI
 
 
 You don&rsquo;t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement &mdash; when that&rsquo;s the case, we'll say so explicitly in the qualifications. People who thrive here don&rsquo;t treat AI as a novelty. They use it to think better, and make their work easier for others to build on.
 
 
 Equal Opportunity &amp; Accommodations
 
 
 We hire talented people from a wide range of backgrounds. If you&rsquo;re excited about this role but don&rsquo;t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know.
 
 
 Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.
 
 
</div>

Software Engineer, New Grad (AI)

Miso Labs

<div>At Miso Labs, our goal is to pass the voice Turing test. In order to do so, we must move beyond the current STT-&gt;LLM-&gt;TTS paradigm, and train full-duplex speech-to-speech models. This requires exploring new architectural ideas, and scaling them rapidly.
We&rsquo;ve raised a large seed round from top investors and are hiring our founding research team. We&rsquo;re a small team, so you can expect to work on every part of the model training stack from small-scale architecture experiments, to large pre-training runs on up to 1000 H100s. We are an in-person culture in San Francisco, and you will be expected to relocate to the SF area (we will cover the moving costs).
It is important to us that team members get credit for their work. Outside of our core IP, researchers are encouraged to publish their work in conferences, and we are happy to sponsor travel to top conferences in AI/ML.
Preferred Qualifications:<ul><li>
Have a Bachelor&rsquo;s Degree in a technical field (Computer Science, Physics, Mathematics etc.) or equivalent experience</li><li>
Excited to work on all aspects of model training and development</li><li>
Are comfortable with both research and hands-on engineering</li><li>
Are capable of owning long-term research outcomes end-to-end</li><li>
Willing to learn technical skills quickly, in a self-directed manner</li><li>
Prior experience with both PyTorch and CUDA</li></ul>
If you&rsquo;re interested in this role, please apply even if you don&rsquo;t fit all the qualifications. We&rsquo;re more interested in evidence of exceptional ability than prior experience in deep learning/AI.
This role comes with full benefits including:<ul><li>
Healthcare, vision, and dental</li><li>
Stipend for gym</li><li>
Relocation bonus</li></ul>
Compensation Range: $400K - $500K</div>

Founding Researcher

David Joseph & Company

<div>San Francisco, CA &middot; On-site &middot; Full-time 
Compensation: $180,000&ndash;$220,000 + competitive equity<h2 class="jobSectionHeader">
About the Company</h2>
An early-stage (post&ndash;Series A) company building the training data and evaluation infrastructure that frontier AI labs use to improve their models &mdash; designing high-signal datasets and running rigorous evaluations that go beyond static benchmarks. A small team where individual contributors have direct impact on how the next generation of models learns. The company has raised $30M (~$300M valuation), with a founding team drawn from Jane Street, Citadel, Google, Goldman, and Stanford AI Lab.
Founded 2025 &middot; 11&ndash;50 people &middot; Industry: Consumer Tech<h2 class="jobSectionHeader">
The Role</h2>
As a SWE (Environments), you'll design the datasets and evaluation rubrics that directly influence how frontier models learn &mdash; going from hypothesis to live experiment quickly, with output feeding directly into model training runs at scale.
What you'll be doing<ul><li>
Design data slices and explore data shapes that expose meaningful model failure modes across domains like finance, code, and enterprise workflows</li><li>
Build and refine evaluation rubrics and reward signals for RLHF and RLVR training pipelines</li><li>
Model annotator behavior and run experiments to improve different model capabilities</li><li>
Develop quantitative frameworks for measuring dataset quality, diversity, and downstream impact on model alignment and capability</li><li>
Create and manage both real-world and synthetic data pipelines</li><li>
Partner with lab research teams to translate their training objectives into concrete data and evaluation specifications</li></ul>
Tech stack: Not specified<h2 class="jobSectionHeader">
Requirements</h2><ul><li>
1&ndash;4 years of software engineering experience with strong technical depth</li><li>
Design targeted data slices that surface model failure modes across high-stakes domains (finance, code generation, enterprise workflows)</li><li>
Build and iterate on evaluation rubrics and reward signals powering RLHF and RLVR training pipelines</li><li>
Develop quantitative frameworks to measure dataset quality, diversity, and downstream impact on model alignment and capability</li><li>
Own end-to-end real world and synthetic data pipelines, from scoping with research teams to production-ready evaluation specs</li><li>
Run annotator modeling experiments to improve model capabilities across task types</li></ul><h2 class="jobSectionHeader">
Green Flags</h2><ul><li>
Experience at RL environment companies</li><li>
Background in AI safety or benchmarking organizations like METR or Artificial Analysis</li><li>
Genuine obsession with how data structure, selection, and quality drive model behavior</li><li>
Ability to design lightweight experiments and move fast</li><li>
Former founders or early engineers at early stage startups</li><li>
Demonstrated ability to work hard, learn fast, and care deeply about details</li></ul><h2 class="jobSectionHeader">
Red Flags</h2><ul><li>
Pure research profile with limited engineering output, this is a SWE role, shipping matters</li><li>
Looking for standard product engineering work &mdash; the real scope is data pipelines, reward modeling, and eval infra</li></ul><h2 class="jobSectionHeader">
Why Join</h2><ul><li>
Outsized total cash: base plus substantial profit share, plus competitive equity</li><li>
Direct impact on frontier AI model development, working with the world's leading AI labs</li><li>
High ownership on a small, early team &mdash; scope, build, and ship end to end</li></ul><h2 class="jobSectionHeader">
Details</h2><ul><li>
Location: San Francisco, CA</li><li>
Work policy: On-site</li><li>
Compensation: $180,000&ndash;$220,000 + equity</li><li>
Visa sponsorship: O-1, OPT</li><li>
Employment type: Full-time</li></ul></div>

Software Engineer, RL Environments

Greptile

<div>
 We want to build agents that autonomously validate code changes. Today that looks like AI that reviews pull requests in GitHub, catching bugs and enforcing standards. We&rsquo;re reviewing close to 1B lines of code a month now for over 3,000 companies.
 
 
 
 Problems We&rsquo;re Excited About
 
 
 
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 Coding standards can be idiosyncratic and are often poorly documented; can we build agents that learn them through osmosis like a new hire might?
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 Can we identify for each customer what types of PR feedback they do and don&rsquo;t care about, perhaps using some sample efficient RL, in order to increase signal-to-noise ratio?
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 Some bugs are best caught by running the code, potentially against discerning AI-generated E2E tests. Can we autonomously deploy feature branches and use agents to parallel try to break the application to detect bugs?
 
 
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 Trajectory
 
 
 
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 7,000+ customers
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 Raised $30M from Benchmark, YC, Paul Graham, Initialized
 
 
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 Team
 
 
 
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 We have assembled a small, talent dense team who have scaled critical functions at companies like Stripe, Google, Figma, LinkedIn, etc.
 
 
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 Qualifications
 
 
 
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 BS in Computer Science or equivalent
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 Some research experience, ideally with ML/LMs/Agents
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 Strong programming skills and good product intuition
 
 
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 Responsibilities
 
 
 
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 Experiment with and apply recent advancements in agents/LMs etc. to improve the performance and capabilities of our products
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 Example: you might study multi-agent architectures, prototype and evaluate a multi-agent code review workflow, and then work with a team to integrate successful prototypes into production systems
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 Stay current with the latest research in LLMs, information retrieval, and developer tooling
 
 
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 Compensation Range: $180K - $280K
 
 
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Research Engineer

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