Live opening · Posted 1 day ago
At a glance
The key details from the original listing.
About the role
Description supplied by the original job listing.
For our client, we are seeking a Staff Machine Learning Engineer to join the team of a leader in the Finance & Insurance space.
This role will shape and deliver production ML systems that improve the customer experience at scale. You will partner closely with technical leadership to define roadmaps, execute quarterly plans, and drive high-impact initiatives from architecture through production. The position blends advanced ML engineering, strong software discipline, and responsible AI practices in a fast-moving, highly regulated environment.
Location: Remote - US based candidates only, no visa sponsorship available
Compensation: $218,025 – $256,500 annually
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
Qualifications
8+ years of experience in machine learning and software engineering, with a focus on production ML systems
Hands-on expertise 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
Benefits
Medical, dental, and vision insurance
401(k) retirement plan with company contributions
Equity and bonus eligibility
Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.
Work arrangement
Yes
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