Machine Learning Engineering Manager

Role Description

As a Machine Learning Engineering Manager on the Responsible AI team (RAI), you will oversee multiple data scientists and machine learning engineers towards the goal of ensuring safe, compliant, and fair AI products for all users of the Indeed platform. You will also work collaboratively with partner teams across the business, including Product, Software Engineering, UX, Legal, and Trust teams.

• Develop sustainable methods that ensure strict standards for all AI products at Indeed.
• Design and build data science tools supporting Indeed's Responsible AI goals, including:
  • Classifiers for verifying safe AI output and preventing sensitive data leakage.
  • Red-teaming agents for stress-testing AI systems for harmful content.
  • Evaluation suites for evaluating AI for compliance, fairness, and safety before they launch.
• Manage multiple data scientists and machine learning engineers.
• Set the technical direction of the science team and drive execution of large-scale initiatives.
• Ensure that your teams deliver high-quality solutions that improve experiences for job seekers and employers.
• Collaborate with your engineering counterpart on the RAI team to move science projects from proof-of-concept to infrastructure.
• Foster an innovative and open team culture while ensuring operational excellence among your team.

Qualifications

• Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field with a minimum of 8 years of related experience; or a Master’s degree with a minimum of 6 years of experience; or a PhD with a minimum of 3 years experience.
• Demonstrated achievement as a Manager in Machine Learning Engineering, overseeing teams of 3 or more, and addressing intricate, large-scale problems.
• Well-versed in coding (Python, Java, Go, or C++) and experience with SQL Databases like Presto, and data processing frameworks like Spark.
• Full-stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring.
• Highly effective in coaching Machine Learning Engineers, facilitating qualification enhancement, and fostering career development.

Requirements

• Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.
• Work to understand, prioritize, and plan the team’s work items without external guidance.
• Ensure delivery of machine learning solutions, set expectations for what can be done and by when, and prioritize incoming projects.
• Improve existing Agile, ML, and A/B testing processes and develop new ones.
• Scope projects, gather and improve on requirements, and delegate work effectively.
• Partner with and provide project direction and feedback to cross-functional peers, including Product Managers and Software Engineers.
• Remove roadblocks and give individual contributors autonomy and ownership.
• Brainstorm with teammates about practical experimental design, navigating production codebases, and model development.
• Be prepared to closely engage and contribute directly to implementation when necessary.

Benefits

• Quarterly bonuses.
• Restricted Stock Units (RSUs).
• Paid Time Off policy.
• Many region-specific benefits.