Engineering Manager, Machine Learning, Ranking

Role overview Lead the machine-learning ranking team responsible for balancing a job marketplace and helping users find relevant opportunities. This management role combines team development, technical guidance, and product planning, with a focus on measurable outcomes and the health of both the models and the engineering environment. The team includes data scientists and machine-learning engineers.

Responsibilities - Coach and support a senior team, including career development, workload planning, and growth opportunities. - Partner with product and decision-science colleagues to shape the roadmap, choose metrics, and define marketplace experiments. - Provide technical leadership in cross-functional work and assess how machine learning and AI are applied. - Guide the design, development, and deployment of models and pipelines for jobseeker behavior and marketplace dynamics. - Monitor model speed and accuracy and help the team improve performance over time.

Requirements - 6+ years in software development at scale and at least 2 years in software engineering leadership. - Experience as an ML manager or as a senior/staff data scientist or machine-learning engineer ready to move into management. - Deep knowledge of machine-learning algorithms and practices, with the ability to assess technical work and guide ML engineers. - Strong computer science fundamentals and coding skills; Python, Java or Scala, and a framework such as TensorFlow, PyTorch, or scikit-learn. - Practical experience applying embeddings or vector methods to business problems. - Ability to build reproducible ML pipelines with experiment tracking, data and model versioning, and controlled environments. - Strong communication skills and experience with B2B or B2C products, including multiple product iterations.

Nice to have A degree in mathematics, computer science, physics, or a related technical field is preferred. Three or more years of engineering management experience and experience solving ambiguous problems with new approaches are also valued.

Benefits and work setup The work environment is hybrid, and most US-based roles can also be performed remotely. The listed US base salary range is $200,000–$265,000. Benefits include flexible paid time off, an employer-matched 401(k), and other medical, financial, and wellbeing benefits; additional compensation may include equity or bonuses.