ML Engineer: Build End-to-End AI Systems & Agents

Lovelace AI, Inc.; Pittsburgh (Allegheny County); On-site; USD 140,000 - 230,000; Full time

Benefits offered by this job

Competitive compensation

Comprehensive benefits

Inclusive work environment

Job summary

Lovelace AI, Inc. is seeking a Machine Learning Engineer to own ML problems end to end, from framing to shipping a production system. You’ll decide data needs, model types, and how the surrounding system should operate, working on a team led by the Chief Scientist.

We value engineers who ramp quickly, possess strong research backgrounds, and can think critically about their own work and agents. Industry experience isn’t required, but demonstrated problem ownership is essential.

Qualifications

• Own ambiguous problems end to end, from problem framing to production.
• Strong ML fundamentals, from probabilistic foundations to large language models.
• Experience building the system around a model: data pipelines, evaluation, deployment, and scale.

Responsibilities

• Frame ambiguous product needs as precise ML problems, and set your own requirements.
• Decide what data is useful, which model types fit, and when to go beyond fine-tuning.
• Direct AI coding agents, review their output critically, and push back when their design decisions are wrong.
• Design the systems around your models: data pipelines, serving, evaluation, and monitoring.
• Choose metrics that reflect real outcomes, and catch when they mislead.
• Stand up new jobs, make changes across the codebase, and ship NLP and LLM systems to production, owning their correctness.
• Challenge assumptions, including teammates' and your own, to get to the right answer.

Skills

Ambiguous problems

End-to-end ownership

ML fundamentals

Python

Model deployment

Tools

Python

Job description

Lovelace AI, Inc. is seeking a Machine Learning Engineer to own ML problems end to end, from framing to shipping a production system. You’ll decide data needs, model types, and how the surrounding system should operate, working on a team led by the Chief Scientist.

We value engineers who ramp quickly, possess strong research backgrounds, and can think critically about their own work and agents. Industry experience isn’t required, but demonstrated problem ownership is essential.