Senior Machine Learning Engineer
Vor 3 Tagen
Boam AI builds managed data solutions that transform messy, unstructured signals from public, private, and proprietary sources into structured, reliable, and always up-to-date intelligence on millions of SMBs and enterprises worldwide. These agentic systems power CRMs, data warehouses, AI products, and mission-critical decisions across the enterprise.
As a Senior Machine Learning Engineer, you will own end-to-end ML systems that power our core product. You'll design and operate scalable ML data pipelines and agentic workflows, ship production-ready LLM and model-driven features, and help guide how new research and techniques make it into production. This is a role for someone who has shipped ML at scale, wants real ownership, and is excited to help set the bar for a small, senior team.
What You'll Do- Own production ML systems end to end: design, ship, operate, and improve
- Build scalable ML pipelines and agentic workflows you can run and trust at scale
- Develop and ship production-ready LLM- and model-driven features
- Collaborate closely with backend, data, and product teams on ML-powered features and APIs
- Guide the adoption of new ML research and techniques into production systems
- Implement and refine experiment tracking, model CI/CD, and automated retraining
- Raise reliability and observability: drift detection, data quality, and regressions
- Help shape our ML/AI architecture, tooling, and best practices
- Mentor ML engineers through design reviews, pairing, and feedback
- 5+ years of ML experience, including owning production ML systems end to end
- Strong Python skills and deep experience with ML or LLM-based systems
- Comfortable designing and operating ML pipelines, feature stores, and evaluation at scale
- Familiarity with modern foundation models and agentic patterns
- Helped engineers level up through feedback and standards
- Evaluated new ML/AI approaches and got the best ones into production
- Bias to ship, measure, and refine rather than chase perfect offline metrics
- Motivated by solving real customer problems and seeing models used in the wild
- Thrive without heavy process, QA buffers, or endless safeguards – you own what you ship
- Join a no-politics, high-trust, low-ego, and high-talent team
- Work on mission-critical ML systems used by top-tier enterprise customers
- Work directly with founders and the Head of Engineering on problems that matter
- High autonomy, real impact, and clear ownership from day one
- Operate at the intersection of AI, data infrastructure, and enterprise workflows
- Top-tier compensation with meaningful equity upside
- Help build the ML platform, patterns, and engineering culture you can be proud of
Our process is fast, structured, and transparent – built to respect your time and surface real mutual fit
1. Intro Call
A short conversation to learn more about you, share context on Boam AI and the role, and answer initial questions
2. Deep Dive
Walk us through past ML work and systems you've led, and how you think about complex, ambiguous modeling and production challenges
3. Work Sample
Solve a real Boam-style ML challenge that shows your modeling approach, system design thinking, and execution muscle
4. Founder / Leadership Conversation
Candid discussion with our founder and Head of Engineering on ambition, values, ownership, and how you'd help us scale our ML and agentic systems and mentor the team.
Apply between Dec 15, 2025 and Jan 10, 2026. After Jan 10, we'll review all applications and quickly invite the candidates we'd like to take forward.
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