Senior ML Engineer

Alliance • New York City, NY

4d • Onsite

About The Position

Alliance is the leading accelerator for crypto & AI founders. Since 2020 we’ve backed 300+ startups (Rain, Pump, Synthetix, Pendle, and many more), now collectively valued at $15B+. We’re hiring a Machine Learning Engineer to join our in-house engineering team. You’ll report directly to Carter (CTO) and will be responsible for owning features from the requirements definition stage to production.

Requirements

• Senior, self-directed ML engineer who can take an ambiguous problem from first experiment through a reliable production release.
• Deep experience with Python and applied machine learning; comfortable moving between data exploration, training code, application code, APIs, and production debugging.
• Strong modeling judgment: problem and label definition, feature design, evaluation, backtesting, leakage, missing data, calibration, interpretability, and model selection.
• Enough software and data engineering depth to ship your own work: build pipelines and services, integrate external APIs, manage model artifacts and schemas, and maintain production workflows without heavy engineering support.
• Practical experience with LLM systems: structured outputs, model and prompt evaluation, observability, retries, cost and latency tradeoffs, and safe handling of untrusted inputs.
• Clear communicator with good product judgment who can work directly with non-technical stakeholders and turn model output into a useful decision or operating tool.
• Extremely high-agency, entrepreneurial, self-driven.
• NYC-based or willing to relocate (non-negotiable).

Nice To Haves

• Shipped ML products that people actually use, with evidence of owning the path from raw data and experimentation through deployment, monitoring, and iteration.
• Strong public work: a standout GitHub, useful open-source contributions, published research, technical writing, or unusually good independent experiments.
• Experience building prediction, ranking, classification, recommendation, or anomaly-detection systems on messy real-world data.
• Experience building LLM evaluation systems, structured extraction pipelines, research agents, or other production AI workflows.
• Founder, early ML hire, or senior individual contributor at a fast-moving startup, especially where you operated without a dedicated ML platform or large engineering team.
• Clear signals of exceptional technical or quantitative ability: strong research, competition results, Math/Physics Olympiad performance, or a top technical academic background.

Responsibilities

• Own applied ML end-to-end: turn a loosely defined problem into a dataset, an experiment, a model, and a production system without relying on a PM or a large engineering team.
• Build and operate production Python systems for data collection, enrichment, feature extraction, scoring, evaluation, and AI-assisted research.
• Develop models people can trust: define labels and features, build evaluation sets and backtests, catch leakage and bad source data, compare approaches, and know when a simpler model is the right answer.
• Move work from the model lab into production: own artifacts, feature and prompt compatibility, APIs, background jobs, observability, failure handling, and releases.
• Improve our LLM systems including structured extraction, research agents, prompt and model evaluation, and the guardrails needed to use untrusted external data safely.
• Work directly with stakeholders to decide what is worth building, explain model behavior and tradeoffs clearly, and iterate based on how the system is actually used.

Benefits

• Work with the most ambitious founders in crypto and AI.
• Learn firsthand from hundreds of startups succeeding – or failing.
• Join a small, high-trust, high-performance team with outsized impact.
• Direct ownership and visibility: your work shapes how the next generation of founders discovers Alliance.
• Career accelerator: this role sets you up, experience- and network-wise, for any high-impact path in crypto/AI – at startups, venture firms, or your own company.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed