Senior ML Engineer
About The Position
MLabs is recruiting a Senior Machine Learning Engineer for a premier venture accelerator that backs high-growth technology and emerging-tech startups. The role is based in New York City and requires working onsite in the office. Reporting directly to the Chief Technology Officer, the engineer will own features across the product lifecycle, from defining requirements through production deployment. The role calls for an entrepreneurial, self-directed approach to turning loosely defined problems into reliable, production-ready machine learning and LLM-based systems, without depending on large engineering teams or dedicated project managers. The engineer will build and operate production ML and LLM systems, work directly with stakeholders to prioritize the roadmap, and communicate model behavior and tradeoffs. The position offers direct partnership with founders, ownership of core systems supporting founder discovery and operational workflows, and work in a lean engineering team. Compensation is $300,000–$375,000, with a competitive compensation and benefits package.
Requirements
- Proven ability to drive complex, ambiguous machine-learning problems from experimentation through reliable production releases.
- Strong Python skills across data exploration, training pipelines, application logic, APIs, and production debugging.
- Deep experience in problem formulation, label definition, feature engineering, evaluation metrics, backtesting, data leakage prevention, calibration, interpretability, and model selection.
- Strong software engineering and data pipeline fundamentals, including the ability to deploy, integrate, manage schemas, and monitor services autonomously.
- Hands-on experience with applied LLM systems, including structured outputs, model and prompt evaluation frameworks, observability, retry strategies, cost and latency optimization, and input validation.
- Ability to communicate technical tradeoffs clearly to non-technical stakeholders and translate model outputs into actionable business tools.
- Based in or willing to relocate to New York City; onsite presence is strictly required.
Nice To Haves
- Track record of shipping customer-facing ML products with end-to-end ownership.
- Strong technical portfolio, such as active GitHub projects, open-source contributions, published research, or technical writing.
- Experience developing prediction, ranking, classification, recommendation, or anomaly-detection systems using messy, real-world data.
- Background building LLM evaluation frameworks, structured extraction pipelines, or automated research agents.
- Early-stage startup experience as a founder, early ML hire, or senior individual contributor without dedicated platform teams.
- Exceptional technical or quantitative background, such as strong research experience, competition achievements, or a top-tier academic background in quantitative disciplines.
Responsibilities
- Translate ambiguous business problems into datasets, experiments, models, and production systems.
- Develop and maintain production Python systems for data collection, enrichment, feature extraction, scoring, model evaluation, and AI-assisted research workflows.
- Define labels and features; build evaluation sets and backtests; identify data leakage; assess source quality; and select appropriate modeling approaches, including traditional machine learning and LLMs.
- Move models from research into production, managing artifacts, feature and prompt compatibility, APIs, background jobs, observability, failure handling, and release cycles.
- Improve LLM systems, including structured data extraction, research agents, prompt and model evaluation, and safety guardrails for untrusted external inputs.
- Work directly with stakeholders to prioritize the roadmap, explain model behavior and tradeoffs, and iterate based on real-world usage.
Benefits
- Competitive compensation and benefits package.
- Direct partnership with high-impact founders across emerging technology sectors.
- High-trust, high-autonomy environment within a lean engineering team composed of industry veterans.
- Direct ownership of core systems shaping founder discovery and operational workflows.
- Accelerated career growth and networking opportunities within a leading startup ecosystem.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
