ML Engineering Manager: Lead AI Systems & Delivery (Equity)

Signifyd; Northern (KY); Hybrid; USD 200,000 - 235,000; Full time

Benefits offered by this job

Discretionary Time Off (Unlimited!)

401K Match

Stock Options

Annual Performance Bonus

Paid Parental Leave (12 weeks)

Health Insurance

Vision Insurance

Learning Budget

Job summary

Signifyd is seeking an Engineering Manager to lead a cross-functional team of engineers, data scientists and product stakeholders. You will drive delivery, mentor engineers, and partner with the AI group to translate ideas into production systems.

You will work closely with data scientists, ML engineers and product owners to ensure reliable, scalable solutions while balancing technical debt and delivery timelines. The role emphasizes people leadership and AI-aware engineering practices.

Qualifications

• 5+ years as a software engineer with ML exposure.
• 4+ years of direct people-management in ML domains.
• Experience in architecture, data flows and reliable systems.
• Proficiency with AI tools for research, admin and code tasks.
• Ability to communicate across technical and non-technical stakeholders.

Responsibilities

• Lead and coach a team of engineers; provide regular feedback and career growth.
• Foster a healthy team culture with ownership and high quality standards.
• Recruit and onboard engineers; develop technical leadership within the team.
• Drive delivery of the team's roadmap balancing features, debt and reliability.
• Participate in architecture decisions and ensure alignment with AI initiatives.

Skills

Software engineering

ML experience

People management

Stakeholder communication

Technical leadership

Tools

Databricks

Spark

Airflow

Vertex AI

GCP stack

Job description

Signifyd is seeking an Engineering Manager to lead a cross-functional team of engineers, data scientists and product stakeholders. You will drive delivery, mentor engineers, and partner with the AI group to translate ideas into production systems.

You will work closely with data scientists, ML engineers and product owners to ensure reliable, scalable solutions while balancing technical debt and delivery timelines. The role emphasizes people leadership and AI-aware engineering practices.