Staff ML Engineer — Production Systems & Responsible AI

Ladders; United States; Remote; USD 218,000 - 257,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) retirement plan with companyCon

Equity and bonus eligibility

Job summary

The Ladders client seeks a Staff Machine Learning Engineer to shape production ML systems and improve customer experience at scale. You will partner with technical leadership to define roadmaps, execute quarterly plans, and drive initiatives from architecture through production in a fast-moving, highly regulated environment.

Responsibilities include designing and delivering production ML systems, mentoring engineers, and ensuring security and responsible AI practices.

Qualifications

• 8+ years in machine learning and software engineering, with a focus on production ML systems.
• Hands-on with LLMs, deep learning, graph neural networks, and advanced statistics.
• Strong Python skills for writing maintainable, tested production code.
• Experience mentoring engineers and influencing technical standards across teams.
• Ability to utilize generative AI responsibly, ensuring human oversight in outputs.

Responsibilities

• Own the design and delivery of production ML systems to enhance customer experience
• Partner with leadership to define strategic roadmaps and execute quarterly plans
• Lead high-impact ML projects from architecture to production, managing risks and priorities
• Build scalable and reliable ML systems and data workflows using high-quality Python code
• Mentor engineers and establish standards for design, testing, and operational excellence
• Drive design reviews focusing on security, responsible AI, and model quality

Skills

ML engineering

Production systems

LLMs

Deep learning

Graph nets

Statistics

Mentoring

Python

Tools

Python

Job description

The Ladders client seeks a Staff Machine Learning Engineer to shape production ML systems and improve customer experience at scale. You will partner with technical leadership to define roadmaps, execute quarterly plans, and drive initiatives from architecture through production in a fast-moving, highly regulated environment.

Responsibilities include designing and delivering production ML systems, mentoring engineers, and ensuring security and responsible AI practices.