ML Engineering Manager - Lead AI Innovation & Risk Insights

Harnham; Chicago (IL); Hybrid; USD 220,000 - 240,000; Full time

Benefits offered by this job

Annual bonus

Equity opportunities

Health benefits

Hybrid work

Job summary

Harnham is seeking a senior ML Engineering Manager to lead a high-performing team of machine learning engineers and applied scientists in Chicago. You will shape roadmaps, guide production ML deployments, and drive experimentation and rigorous evaluation to deliver measurable business impact.

The role requires 5+ years in ML/Data Science and 2+ years of people management, with strong communication, collaboration with business stakeholders, and a track record of delivering complex models in risk

Qualifications

• 5+ years of experience in Machine Learning, Data Science, Applied AI, or related software engineering disciplines.
• At least 2 years of people management experience (3+ direct reports).
• Strong technical depth in ML, statistics, software engineering, or related fields.
• Experience deploying production ML models in large-scale environments, e.g., credit risk or fraud.
• Proven ability to lead in ambiguity and data-driven decision making.

Responsibilities

• Lead, mentor, and develop a team of ML engineers and scientists.
• Shape the ML roadmap and oversee model development lifecycle from training to production.
• Collaborate with business and technical stakeholders to translate model results into impact.
• Drive experiments, evaluate results rigorously, and prioritize resources.

Skills

Machine Learning

Applied AI

Data Science

Team Leadership

Technical Interviewing

Model Evaluation

Bayesian Statistics

Causal Inference

Experimentation

Stakeholder Communication

Tools

Python

Job description

Harnham is seeking a senior ML Engineering Manager to lead a high-performing team of machine learning engineers and applied scientists in Chicago. You will shape roadmaps, guide production ML deployments, and drive experimentation and rigorous evaluation to deliver measurable business impact.

The role requires 5+ years in ML/Data Science and 2+ years of people management, with strong communication, collaboration with business stakeholders, and a track record of delivering complex models in risk