Founding Machine Learning Engineer
Stealth Startup | San Francisco, California, United States | 1mo ago
This role has closed. Here are similar open builder roles:
| 1. | AI Builder Intern - Agentic AI (Mondee) Austin, Texas, United States | on-site | internship | internship | ai, agentic ai, llms | 2w ago |
| 2. | AI Systems Weirdo (UniteGPS) South Portland, ME, United States | on-site | full-time | mid | ai systems design, route optimization, gps tracking | 2w ago |
| 3. | Software Engineering Intern (Maritime Technology Startup (Stealth)) El Segundo, California, United States | $40 – $48/hr | on-site | internship | internship | python, go, javascript | 2w ago |
| 4. | AI-Native Founding Engineer (Jobright.ai) San Francisco, California, United States | $130,000 – $170,000/yr | on-site | full-time | lead | typescript, react, sql | 2w ago |
| 5. | MLE @ Krnel (NYC, Full-Time) (krnel.ai) New York, New York, United States | on-site | full-time | mid | machine learning, devops, ci/cd | 2w ago |
| 6. | AI Builder Intern - Agentic AI (Tabhi) Austin, Texas, United States | on-site | internship | internship | agentic ai, llms, agent frameworks | 2w ago |
| 7. | Forward Deployed Engineer (Legion Intelligence) Washington DC, United States | $185,000 – $260,000/yr | on-site | full-time | mid | python, javascript, typescript | 2w ago |
| 8. | Senior Founding Engineer (Ambral) New York City, New York, United States | $185,000 – $245,000/yr | on-site | full-time | senior | typescript, nuxt, postgres | 2w ago |
| 9. | Full-Stack Engineer- Series B Ai · $200-300K + equity (Benchstack Ai) San Francisco, California, United States+1 | $200,000 – $300,000/yr | on-site | full-time | senior | react, typescript, python | 2w ago |
| 10. | Marketing Productivity Engineer (Sigma Computing) San Francisco, United States+2 | $130,000 – $165,000/yr | on-site | full-time | senior | performance marketing, growth engineering, marketing operations | 2w ago |
Original posting (closed) below
full-time | on-site | senior | 4–10 years | visa sponsorship
skills: llm agents, time-series modeling, agent development, multi-step reasoning, tool integration, autonomous workflows, memory management, context management, adaptive strategies, evaluation frameworks, forecasting, anomaly detection, multimodal fusion, data ingestion, preprocessing, deployment, monitoring, mlops, ci/cd, observability, transformers, deep learning, neural networks
We're hiring our Founding Machine Learning Engineer (MLE) with expertise in Agent Development and Time-Series Modeling. You'll play a foundational role in building production-grade systems that combine the power of LLM-powered agents with time-series foundation models.
The Role
This is not a narrow research role — you'll design, train, deploy, and monitor ML systems end-to-end, moving from prototype to production with speed and autonomy. You'll also be a core contributor to defining how agents interact with multimodal numerical data, a problem space where the playbook does not yet exist.
Job Description:
- Design, train, and deploy production ML systems (LLM-powered agents + time-series models)
- Build and scale LLM-powered agents with advanced capabilities: multi-step reasoning, tool integration, autonomous workflows, memory/context management, and adaptive strategies
- Develop and refine evaluation frameworks for agents, ensuring reliability, safety, and measurable performance
- Apply and extend time-series modeling techniques (forecasting, anomaly detection, multimodal fusion) in real-world customer scenarios
- Operate end-to-end: from data ingestion and preprocessing to deployment, monitoring, and continuous improvement
- Stay ahead of the curve on the latest innovations in AI agents, orchestration frameworks, and infrastructure (MCP, A2A, etc.)
- Partner directly with researchers, engineers, and lighthouse customers to validate solutions and drive rapid iteration
What we're looking for:
- Proven industry experience (4-10 years) as an ML Engineer, Research Engineer, or Applied Scientist, with a track record of shipping production ML systems
- Hands-on expertise in LLM-powered agents: multi-step reasoning, tool use, context windows, autonomous workflows, agent memory
- Deep understanding of agent evaluation techniques (reliability, safety, success metrics)
- Up-to-date with modern agent infrastructure and frameworks (MCP, A2A, etc.)
- Fluency with ML engineering best practices: reproducibility, monitoring, scaling, CI/CD, observability
- Comfort operating in a fast-paced startup: shipping quickly, making tradeoffs, and thriving in ambiguity
Nice to have:
- Experience training custom neural networks beyond pre-trained LLMs (e.g., transformers for time-series or multimodal data)
- A background in time-series modeling (forecasting, anomaly detection, classical + deep learning approaches)
- Published research or open-source contributions in ML/AI
Location & Sponsorship
- Location: San Francisco Bay Area, CA (in-person)
- Visa Sponsorship: H1-B, O1
Get new builder jobs daily: