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Smvsoft LLC

<p><b>Founding Engineer - Applied AI</b><br/>San francisco, CA (Full time)- In-Office</p><p>$180k-$230k per annum</p><p><b>NO C2C</b></p><p><b>About the Role</b></p><p>Hiring a world-class Applied AI Engineer to build the core systems behind their automation engine for hardware engineering.</p><p>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.</p><p><b>Key Responsibilities</b></p><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><p><b>Requirements</b></p><p><b>Must-Have</b></p><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><p><b>Nice-to-Have</b></p><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><p>Pay: $180,000.00 - $230,000.00 per year</p><p>Work Location: In person</p>

Founding Engineer - Applied AI

Capgemini

<div><div><div><div><p>Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you&rsquo;d like, where you&rsquo;ll be supported and inspired by a collaborative community of colleagues around the world, and where you&rsquo;ll be able to reimagine what&rsquo;s possible. Join us and help the world&rsquo;s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.</p>
<div><div><div><h2 class="jobSectionHeader"><b>Location</b></h2>
</div><div><p>San Francisco CA</p>
</div></div><div><div><h2 class="jobSectionHeader"><b>Your Role</b></h2>
</div><div><p>The GenAI Engineer / Data Scientist is responsible for designing, developing, deploying, and maintaining Generative AI (GenAI) and Predictive AI solutions that deliver business value. The role requires expertise in AI/ML, cloud platforms, APIs, data engineering, MLOps, and AI agent workflows, with a strong focus on production-grade AI implementation.</p><br>
<p><br>
<b>Key Responsibilities</b><br>
</p><p><br>
Develop and deploy Generative AI solutions (GPT, Claude, Stable Diffusion) and Predictive AI models (regression, classification, clustering).
<br>
Design and integrate AI applications using REST APIs, authentication mechanisms, JSON services, and cloud-based architectures.
<br>
Build and support AI agents, autonomous systems, and agentic workflows.
<br>
Deploy, monitor, and optimize AI models in production using MLOps practices.
<br>
Design and maintain data pipelines, data lakes, and data warehouses.
<br>
Monitor model performance, troubleshoot issues, and manage data/model drift.
<br>
Collaborate with business and technical teams to align AI solutions with organizational objectives.
<br>
Create reusable assets, demos, and proof-of-concepts to support innovation and business development.<br>
<br>
<br>
</p></div></div><div><div><h2 class="jobSectionHeader"><b>Required Skills and Experience
</b></h2></div><div><p>A hands-on AI professional with strong expertise in Generative AI, Machine Learning, Python, Cloud Technologies, APIs, MLOps, Data Engineering, and AI Agents, capable of building and scaling enterprise-grade AI solutions from development to production.
<br>
Bachelor's degree or higher in AI, Machine Learning, Computer Science, or related field.
<br>
3-5 years of experience in AI, Machine Learning, Data Science, or Application Development.
<br>
Experience with production AI deployments, MLOps, model monitoring, and cloud platforms.</p>
<p>GPT, Claude LLM, Stable Diffusion
<br>
LangChain
<br>
TensorFlow
<br>
PyTorch
<br>
Scikit-learn
<br>
RAG (Retrieval-Augmented Generation)
<br>
AI Agents &amp; Agentic Workflows
<br>
API Development
<br>
REST APIs
<br>
JSON
<br>
HTTP Requests
<br>
Authentication &amp; Tokens
<br>
Error Handling &amp; Debugging<br>
<br>
<br>
<br>
<br>
</p></div></div></div><p>The base compensation range for this role in the posted location is $90,000- $160,000</p>
<p>Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.</p>
<p>The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.</p>
<p>These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.</p>
<p>It is not typical for candidates to be hired at or near the top of the posted compensation range.</p>
<p>In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.</p>
<p><b>Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees.</b> In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:</p>
<ul><li>Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave</li>
</ul><ul><li>Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)</li>
<li>Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)</li>
<li>Life and disability insurance</li>
<li>Employee assistance programs</li>
<li>Other benefits as provided by local policy and eligibility</li>
</ul><p><b>Important Notice:</b> Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini&rsquo;s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.</p>
<p><b>Disclaimers</b></p>
<p>Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.</p>
<p>This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.</p>
<p>Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.</p>
<p>Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law</p>
<p>Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.</p></div></div></div></div>

Data Scientist/ AI Engineer

David Joseph & Company

<div><p><b>San Francisco, CA &middot; On-site &middot; Full-time</b><br>
<b>Compensation:</b> $180,000&ndash;$220,000 + competitive equity</p><h2 class="jobSectionHeader"><b>
About the Company</b></h2><p>
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.</p><p>
Founded 2025 &middot; 11&ndash;50 people &middot; Industry: Consumer Tech</p><h2 class="jobSectionHeader"><b>
The Role</b></h2><p>
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.</p><p><b>
What you'll be doing</b></p><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><p><b>
Tech stack:</b> Not specified</p><h2 class="jobSectionHeader"><b>
Requirements</b></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"><b>
Green Flags</b></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"><b>
Red Flags</b></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"><b>
Why Join</b></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"><b>
Details</b></h2><ul><li><b>
Location:</b> San Francisco, CA</li><li><b>
Work policy:</b> On-site</li><li><b>
Compensation:</b> $180,000&ndash;$220,000 + equity</li><li><b>
Visa sponsorship:</b> O-1, OPT</li><li><b>
Employment type:</b> Full-time</li></ul></div>

Software Engineer, RL Environments

Stitch Fix

<div><div><h3 class="jobSectionHeader"><b>About Stitch Fix, Inc.
</b></h3><p>Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we're equally committed to building yours. We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what's possible for our clients, while we help you reach your full potential.</p></div><br>
<p></p>
<h1 class="jobSectionHeader"><b>
About the Role</b></h1>
<p>
The Client Experience Product Algorithms team is responsible for the machine learning, AI, experimentation, and product analytics capabilities that power personalized experiences for Stitch Fix clients and stylists. Partnering across Product, Engineering, Design, Styling, Marketing, Merchandising, Finance, Enterprise Analytics, Data Platform, and DSN, the team translates data and algorithms into measurable business impact.</p>
<p>
As Director, Product Algorithms, you will lead the strategy, execution, and people behind our Growth, Styling, and Fix &amp; Freestyle Algorithms portfolios. You'll define how AI, machine learning, experimentation, and analytics shape the future of personalized shopping while building the operating discipline, technical excellence, and cross-functional alignment needed to deliver scalable business results.</p>
<h2 class="jobSectionHeader"><b>
Responsibilities</b></h2>
<ul><li><b>Lead</b> the Product Algorithms portfolio across Growth, Styling, and Fix &amp; Freestyle, setting strategy and driving measurable outcomes across acquisition, engagement, retention, styling quality, Fix, Freestyle, outfitting, and related commerce experiences.</li>
<li><b>Define</b> the vision and roadmap for applying data science, machine learning, AI, experimentation, and product analytics to improve client experiences, stylist effectiveness, and business performance.</li>
<li><b>Drive</b> innovation by identifying, evaluating, and scaling modern AI, machine learning, personalization, and experimentation techniques that create meaningful impact while balancing technical feasibility, execution capacity, and business priorities.</li>
<li><b>Strengthen</b> organizational effectiveness by improving planning, prioritization, experimentation practices, product analytics capabilities, operational readiness, incident management, and cross-functional decision making across the portfolio.</li>
<li><b>Build</b> and develop a high-performing organization of managers and senior individual contributors, fostering technical excellence, strong product leadership, accountability, and collaborative partnerships while representing Product Algorithms with executive stakeholders.</li>
</ul><h2 class="jobSectionHeader"><b>How AI and Tools Show Up in Your Day-to-Day Work</b></h2>
<ul><li>Use AI-powered tools (such as ChatGPT, GitHub Copilot, and other emerging technologies) to improve decision making, productivity, communication, and operational efficiency.</li>
<li>Leverage experimentation platforms, analytics tools, machine learning infrastructure, and product development systems to guide roadmap decisions and measure business impact.</li>
<li>Continuously evaluate and adopt new AI capabilities, technologies, and ways of working that improve team effectiveness and accelerate innovation.</li>
</ul><h1 class="jobSectionHeader"><b>About You</b></h1>
<p>
You are a strategic technical leader who combines deep expertise in machine learning and AI with exceptional product thinking, organizational leadership, and business judgment. You thrive in highly collaborative environments, enjoy solving ambiguous problems, and know how to translate emerging technologies into measurable customer and business outcomes.</p>
<h2 class="jobSectionHeader"><b>
Requirements</b></h2>
<ul><li>Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, or a related quantitative field; advanced degree preferred.</li>
<li>10+ years of experience in data science, machine learning, experimentation, product analytics, AI, or algorithmic product development, including 5+ years leading teams and experience managing managers or senior technical leaders.</li>
<li>Demonstrated success defining strategy and delivering production machine learning, AI, personalization, or experimentation capabilities that drive measurable product and business outcomes.</li>
<li>Strong technical fluency across modern machine learning, generative AI/LLMs, experimentation methodologies, product analytics, and production algorithmic systems.</li>
<li>Experience building cross-functional partnerships with Product, Engineering, Design, Analytics, Data Platform, Marketing, Merchandising, Finance, and executive stakeholders.</li>
<li>Exceptional strategic thinking, communication, prioritization, problem-solving, and organizational leadership skills, with the ability to influence across technical and non-technical audiences.</li>
<li>Experience using AI tools (such as ChatGPT, GitHub Copilot, or similar technologies) to improve productivity, decision making, collaboration, and the quality of work.</li>
<li>This position requires the ability to sit for extended periods of time, use a computer and standard office equipment, and communicate effectively in both written and verbal formats.</li>
</ul><h2 class="jobSectionHeader"><b>Nice to Have</b></h2>
<ul><li>Advanced degree (MS or PhD) in Computer Science, Machine Learning, Statistics, Operations Research, Engineering, or a related field.</li>
<li>Experience leading AI- or ML-driven consumer products within e-commerce, marketplaces, retail, recommendations, personalization, or digital consumer experiences.</li>
<li>Experience building or evolving experimentation platforms, product analytics capabilities, or AI governance and operational excellence practices.</li>
<li>Familiarity with large-scale recommendation systems, ranking models, generative AI applications, causal inference, optimization, or reinforcement learning.</li>
<li>Experience leading organizations through significant technical transformation, organizational scaling, or AI adoption initiatives.</li>
</ul><div><p><i>
This link</i><i> leads to the machine readable files that are made available in response to the federal Transparency in Coverage Rule and includes negotiated service rates and out-of-network allowed amounts between health plans and healthcare providers. The machine-readable files are formatted to allow researchers, regulators, and application developers to more easily access and analyze data.</i></p>
<p>
Please review Stitch Fix's US Applicant Privacy Policy and Notice at Collection here: https://stitchfix.com/careers/workforce-applicant-privacy-policy</p>
<p><b>
Recruiting Fraud Alert:</b></p>
<p>
To all candidates: your personal information and online safety are top of mind for us. At Stitch Fix, recruiters only direct candidates to apply through our official career pages at https://www.stitchfix.com/careers/jobs or https://web.fountain.com/c/stitch-fix.</p>
<p>
Recruiters will never request payments, ask for financial account information or sensitive information like social security numbers. If you are unsure if a message is from Stitch Fix, please email careers@stitchfix.com.</p></div></div><p></p>

Director, Data Science & Algorithms - CX Product Experiences

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.
 <br/>
 <br/>
 <strong>
  Problems We&rsquo;re Excited About
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Coding standards can be idiosyncratic and are often poorly documented; can we build agents that learn them through osmosis like a new hire might?
  </li>
  <li>
   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?
  </li>
  <li>
   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?
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Trajectory
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   7,000+ customers
  </li>
  <li>
   Raised $30M from Benchmark, YC, Paul Graham, Initialized
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Team
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   We have assembled a small, talent dense team who have scaled critical functions at companies like Stripe, Google, Figma, LinkedIn, etc.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   BS in Computer Science or equivalent
  </li>
  <li>
   Some research experience, ideally with ML/LMs/Agents
  </li>
  <li>
   Strong programming skills and good product intuition
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experiment with and apply recent advancements in agents/LMs etc. to improve the performance and capabilities of our products
  </li>
  <li>
   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
  </li>
  <li>
   Stay current with the latest research in LLMs, information retrieval, and developer tooling
   <br/>
   <br/>
  </li>
 </ul>
 Compensation Range: $180K - $280K
 <br/>
 <br/>
</div>


Research Engineer

<div><p><b>San Francisco, CA &middot; On-site &middot; Full-time</b><br>
<b>Compensation:</b> $120,000&ndash;$300,000 + Competitive Equity</p><h2 class="jobSectionHeader"><b>
About the Company</b></h2><p>
An early-stage, venture-backed FinTech building AI compliance analysts that automate AML, KYC, KYB, and transaction monitoring end-to-end for banks and fintechs. The product operates inside browsers, APIs, and internal systems the way a human analyst would, and is already live with financial institutions across multiple regions.</p><p>
Founded 2024 &middot; Seed stage &middot; Small team &middot; Industry: FinTech</p><h2 class="jobSectionHeader"><b>
The Role</b></h2><p>
A backend-leaning Member of Technical Staff building the end-to-end systems that power production AI compliance workflows &mdash; high-performance infrastructure, reliability, and backend architecture supporting mission-critical automation.</p><p><b>
What you'll be doing</b></p><ul><li>
Architect agent behaviors and build the backend systems behind production AI compliance workflows</li><li>
Build browser agents that navigate legacy systems, portals, and third-party platforms, interpreting unstructured data</li><li>
Process risk signals at the speed money moves &mdash; millions of transactions, sub-second decisions &mdash; via distributed inference, caching, queue orchestration, and self-healing data pipelines on AWS</li><li>
Contribute to an in-house deep-research pipeline that keeps LLMs from conflating similar entities</li><li>
Optimize ML pipelines and ship product features, owning problems vertically</li></ul><p><b>
Tech stack:</b> Python, AWS; browser automation, computer vision, LLM systems.</p><h2 class="jobSectionHeader"><b>
Requirements</b></h2><ul><li>
Experience with backend development and/or ML, especially in Python and AWS</li><li>
Hands-on experience deploying software to production environments</li><li>
Strong communication skills and willingness to interact with clients</li></ul><h2 class="jobSectionHeader"><b>
Green Flags</b></h2><ul><li>
Experience with browser automation and computer vision</li><li>
Background with distributed inference and optimization on AWS</li><li>
Familiarity with LLM systems and deep research pipelines</li><li>
Experience building systems that process millions of transactions at scale</li><li>
Knowledge of compliance, AML, KYC, or financial crime domains</li><li>
Competitive coding background</li><li>
Contributions to open-source projects or personal projects on GitHub</li><li>
Prior experience as a founder or at an early-stage startup</li></ul><h2 class="jobSectionHeader"><b>
Red Flags</b></h2><ul><li>
Candidates from a pure data science background who lack strong technical skills</li><li>
Lack of hands-on experience deploying software to production</li><li>
Primarily academic or research experience without practical engineering work</li></ul><h2 class="jobSectionHeader"><b>
Why Join</b></h2><ul><li>
Build frontier AI agents in production, solving hard problems with no off-the-shelf answers</li><li>
Large, underserved market with real customer traction and measurable impact</li><li>
Small team with wide surface area &mdash; own features end-to-end across backend, ML, and product</li></ul><h2 class="jobSectionHeader"><b>
Details</b></h2><ul><li><b>
Location:</b> San Francisco, CA</li><li><b>
Work policy:</b> On-site</li><li><b>
Compensation:</b> $120,000&ndash;$300,000 + equity</li><li><b>
Visa sponsorship:</b> H-1B, O-1, OPT</li><li><b>
Experience:</b> 1+ years</li><li><b>
Employment type:</b> Full-time</li></ul></div>

Member of Technical Staff

<div><p><b>San Francisco, CA &middot; On-site &middot; Full-time</b><br>
<b>Compensation:</b> $130,000&ndash;$150,000 base (up to $300K total cash comp) + equity</p><h3 class="jobSectionHeader"><b>
About the Company</b></h3><p>
A fast-growing, venture-backed AI company building the training data and evaluation infrastructure that leading frontier AI labs use to improve their models &mdash; designing high-signal datasets and running rigorous evaluations that go beyond static benchmarks. One of the fastest-growing companies in its cohort.</p><p>
Founded 2025 &middot; 11&ndash;50 people &middot; Industry: AI training data &amp; model evaluation infrastructure</p><h3 class="jobSectionHeader"><b>
The Role</b></h3><p>
A founding-level role at the intersection of technical execution and strategic leadership. You'll own high-impact initiatives end-to-end &mdash; from requirements through delivery &mdash; managing teams of engineers, data scientists, and ML specialists while shipping production code yourself, and interfacing directly with research teams at leading AI labs.</p><p><b>
What you'll be doing</b></p><ul><li>
Own end-to-end technical initiatives: scoping requirements, building solutions, managing experts through delivery, and shipping code yourself when it unblocks the team.</li><li>
Design and build technical infrastructure and tooling for dataset generation, quality control, and delivery pipelines across multiple concurrent lab contracts.</li><li>
Manage and mentor teams of software engineers, data scientists, and ML specialists; set technical direction and hold the bar for execution velocity.</li><li>
Interface directly with research teams at leading AI labs to translate their needs into technical specs and ensure delivery meets their standards.</li><li>
Debug production issues live under pressure; rapidly context-switch between hands-on engineering, team leadership, and strategic problem-solving.</li><li>
Support the founding team on the highest-impact work &mdash; internal tooling, major contracts, and hiring.</li></ul><p><b>
Tech stack:</b> Python; data pipelines, APIs, ML/AI tooling</p><h3 class="jobSectionHeader"><b>
Requirements</b></h3><ul><li>
CS degree, engineering experience, or equivalent demonstrated ability to ship technical projects</li><li>
Manage teams of technical experts across software engineering, data science, and machine learning</li><li>
Build technical infrastructure and tooling for dataset generation, quality control, and delivery pipelines</li><li>
Drive technical and operational initiatives end-to-end: scoping requirements, building solutions, and managing technical experts</li><li>
Interface directly with engineering and research teams at leading AI labs</li><li>
Support founding team on high-priority technical projects and operational initiatives</li><li>
Proficiency in Python and production-quality code</li><li>
Experience with data pipelines, APIs, or ML/AI tooling</li><li>
Strong leadership experience and communication skills</li><li>
Ability to context-switch rapidly between technical and strategic work</li><li>
Intense work ethic, agency, and drive</li><li>
Competitive nature and track record of exceptional achievement</li><li>
Undergraduate degree from the U.S., Canada, or the U.K.</li></ul><h3 class="jobSectionHeader"><b>
Green Flags</b></h3><ul><li>
Background in software engineering, ML engineering, AI research, or computer science</li><li>
Experience at top tech company (FAANG, frontier AI lab) or quantitative trading firm</li><li>
Prior startup experience or founding experience</li><li>
Willingness to work long hours and weekends when projects demand it</li></ul><h3 class="jobSectionHeader"><b>
Red Flags</b></h3><ul><li>
Worked cushy tech jobs (FAANG PM, etc.) and may not be used to intense work environments.</li><li>
Struggles with ambiguity or lacks examples of owning large, complex projects.</li><li>
Only interested in remote work &mdash; role is strictly in-person.</li><li>
Can't articulate why they want to pivot into AI ops or join a startup now.</li><li>
No experience managing teams or unclear on motivating people toward execution.</li></ul><h3 class="jobSectionHeader"><b>
Why Join</b></h3><ul><li>
Direct access to the founding team on their highest-priority problems</li><li>
Exposure to leading frontier AI labs; work that powers major contracts</li><li>
Up to $300K total cash comp plus meaningful equity in a fast-scaling company</li></ul><h3 class="jobSectionHeader"><b>
Details</b></h3><ul><li><b>
Location:</b> San Francisco, CA</li><li><b>
Work policy:</b> On-site &mdash; strictly in-person</li><li><b>
Compensation:</b> $130,000&ndash;$150,000 base (up to $300K total cash comp) + equity</li><li><b>
Visa sponsorship:</b> None available</li><li><b>
Employment type:</b> Full-time</li></ul></div>

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