Senior ML Engineering Manager (Remote) - Lead ML Teams

Signifyd; United States; Remote; USD 200,000 - 245,000; Full time

Benefits offered by this job

Discretionary Time Off (Unlimited)

401K Match

Stock Options

Annual Performance Bonus

Paid Parental Leave

Health Insurance

Dental Insurance

Vision Insurance

FSA

Disability Insurance

Life Insurance

Company Social Events

Signifyd Swag

Job summary

Signifyd AI Lab (SAIL) builds the ML products behind Signifyd's fraud and risk decisions. We improve the predictive performance of models that decide e-commerce transactions at scale, while expanding capabilities and market reach.

Join us to lead a hands-on team in an environment where experimentation, code, and statistics blend, surfacing from the ground up to inform business outcomes and growth through 2027 and beyond.

Qualifications

• 5+ years in ML, data science, or ML-adjacent software engineering, with 3+ years of people management.
• Depth in engineering or applied statistics, and working competence in the other.
• Experience leading work under uncertainty and communicating results clearly.
• Excellent written and verbal communication; autonomous prioritization and prioritizing impact.

Responsibilities

• Lead and grow the team, mentor engineers, and set goals to foster a positive, high-performing culture.
• Run a portfolio of experiments, pressure-test ideas, allocate resources, and document outcomes.
• Set direction from data in partnership with Risk, balancing research bets with delivery commitments.
• Own delivery cadence, ensure end-to-end evaluation, and ship when value is demonstrated.
• Represent the team’s results to engineering leadership, Risk, and the wider company.

Skills

Leadership

People management

Machine learning

Communication

Job description

Signifyd AI Lab (SAIL) builds the ML products behind Signifyd's fraud and risk decisions. We improve the predictive performance of models that decide e-commerce transactions at scale, while expanding capabilities and market reach.

Join us to lead a hands-on team in an environment where experimentation, code, and statistics blend, surfacing from the ground up to inform business outcomes and growth through 2027 and beyond.