Senior ML Engineer

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• Senior ML Engineer
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Senior ML Eng

Location: 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.

*What You’ll Do*

• 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.

*What We’re Looking For*

• 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).

Examples of strong qualifications (good to have but not required)

• 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.

Why NOT join us

• 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.

Why join us

• 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.
• Apply To Position
• Apply Using LinkedIn

Senior ML Eng

Location: 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.

*What You’ll Do*

• 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.

*What We’re Looking For*

• 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).

Examples of strong qualifications (good to have but not required)

• 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.

Why NOT join us

• 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.

Why join us

• 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.