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Alliance is hiring a Senior, self-directed Machine Learning Engineer to join our NYC team onsite. You’ll own features from requirements through production, building production Python systems for data collection, feature extraction, and scoring.
You’ll lead model development with rigorous evaluation, backtests, leakage checks, and robust deployment practices. You’ll work closely with stakeholders to define priorities, explain model behavior, and ensure responsible AI use.
NYC (onsite only – not remote)
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.
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).
Not willing to get hands dirty: doesn’t matter how important you were in past organizations; at Alliance we’re all builders, not managers (even though many of us were managers in past lives).
Prioritizing work/life balance: this role demands focus, hunger, and a career-defining level of commitment. You must be locked in.
Low agency: if you need someone else to set your priorities or keep you on track, you will fail.
You can’t relocate to NYC. This is non-negotiable: our founders are here, and so are we.
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. We’re ex-Meta, WhatsApp, Coinbase, YC, and have collectively founded multiple venture-backed startups.
We’re backed by S-tier investors including Initialized Capital, Founders Fund, Multicoin, and Dragonfly, along with angels such as Balaji Srinivasan (ex-Coinbase CTO), Kevin Weil (CPO at OpenAI), Kevin Lin (Twitch co-founder), and Jeremy Allaire (Circle CEO), among many others.
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.
Alliance startups are reinventing industries – from media to payments – and improving the lives of everyday people. You’ll have a front-row seat as they change the world.
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.
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.
Experience building prediction, ranking, classification, recommendation, or anomaly-detection systems on messy real-world data. (Strong Qualifications)
New York, US (Office) - Must be able to work office based in NYC
$300K - $375K
The leading crypto accelerator and founder community