Senior ML Engineer: Build Production-Ready ML in NYC

HireChain Ltd; New York (NY); Hybrid; USD 300,000 - 375,000; Full time

Job summary

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.

Qualifications

• Senior, self-directed ML engineer who can take an ambiguous problem through production.
• Deep experience with Python and applied machine learning; capable across data exploration, training, APIs, and production debugging.
• Strong modeling judgment: labels, features, evaluation, backtesting and data leakage handling.
• Enough software and data engineering depth to ship own work with pipelines and external APIs.
• Practical experience with LLM systems: evaluation, observability, retries, and safe data handling.

Responsibilities

• Own applied ML end-to-end and turn problems into datasets, experiments, and production systems.
• Build and operate production Python systems for data collection, enrichment, and feature extraction.
• Develop trustworthy models with proper evaluation, backtests, and leakage checks.
• Move models from lab to production, owning APIs, jobs, and releases.
• Improve LLM systems with structured extraction, prompts, evaluation, and safe data use.
• Collaborate with stakeholders to decide what to build and explain model tradeoffs.

Skills

Python

Applied ML

Production debugging

LLM systems

Stakeholder communication

Tools

APIs

Data pipelines

Job description

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.