Staff Machine Learning Engineer

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 Staff Machine Learning Engineer, you will set the technical direction for how ML, LLMs, and agents power our platform. You will architect advanced ML systems, define standards for training and deployment, and own the reliability and quality of ML across the company. This is a role for someone who has led ML and LLM systems at scale, mentors senior engineers, and wants to shape both the architecture and roadmap of a small, senior team.

What You'll Do

• Set ML technical direction and roadmap: architecture, standards, and the next platform bets
• Architect ML systems that blend classic models with LLM and agentic patterns
• Own ML + agent workflows for entity resolution, attribute extraction, and verification
• Build the shared pipelines and tooling that run those workflows at scale
• Define standards for model training, deployment, and evaluation
• Own reliability and quality metrics: evals, drift, and regressions
• Lead technical design for ML-powered agents across multiple teams
• Drive cross-functional technical decisions on ML tradeoffs: quality, cost, latency, reliability
• Guide adoption of new ML and LLM research into production
• Mentor ML engineers, including seniors, through feedback and design reviews

You Might Be a Fit If...

• 8+ years ML or AI engineering experience, including production ownership
• Have architected LLM or agentic systems in real production environments
• Strong Python skills and deep experience with ML infrastructure, pipelines, and evaluation
• Comfortable designing high-throughput distributed ML systems and data flows
• History of mentoring senior AI engineers and guiding their growth
• Experience defining AI technical strategy and roadmaps for teams or orgs
• Comfortable evaluating and introducing new ML tools, frameworks, and patterns
• Bias to ship, measure, and refine while investing in key foundations
• Motivated by hard real-world data problems and critical workflows

Why Boam AI

• Join a no-politics, high-trust, low-ego, high-talent team
• Own mission-critical ML and agent systems for enterprise customers
• Work directly with founders, Head of Engineering, and engineering leaders
• High autonomy, clear ownership, and visible impact from day one
• Operate at the intersection of AI, data, and enterprise workflows
• Top-tier compensation with meaningful equity participation
• Help shape the ML platform, patterns, and culture of the company

Our hiring process