Senior Machine Learning Engineer

About this Senior Machine Learning Engineer:

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

Position Overview:

Own applied Machine Learning Engineer 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.

What We’re Looking For In A Senior ML Engineer

We value diversity of experience and are looking for individuals passionate about solving complex problems. 

Responsibilities:

• 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).

Preferred Qualifications (for Senior Levels):

• 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.

Compensation For Senior Backend Engineer Job:

SALARY: $150000 – $300000 / year
WORK TYPE: On-site
EMPLOYMENT TYPE: full-time