Engineering Manager, Machine Learning, Ranking

We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.)

Job description

We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.)

Summary:

Our marketplace team builds the specialized products, platforms, and intelligence systems that power our Enterprise customer segment:

• Marketplace Optimization: We use machine-learning and AI techniques to optimize our job marketplace to show jobseekers the right job at the right time, and satisfying the employers who expect results for the job listings they sponsor. Four out of five employers who post a job on ZipRecruiter get a qualified candidate within the first day, and it’s our team’s responsibility to make sure that continues to be true.

Key Focuses:

We are seeking an Engineering Manager to lead our Ranking team within our Marketplace organization. This is a high-priority, high-impact role where you will lead a highly capable, senior team of Data Scientists and Machine Learning Engineers. We're looking for engineering managers who can own entire (or even multiple) product lines, drive business value while investing in their team's/tech stack's health, and coach engineers to build a strong culture of excellence, ownership, and personal and professional growth.

• Lead and support a senior team (Data Scientists, Generalists, and MLEs), driving career development, workload balancing, and growth opportunities.
• Partner closely with Product Management and Decision Science to shape the product roadmap, define metrics, and establish success criteria for marketplace balancing tests.
• Evaluate day-to-day technical work, ensuring effective use of ML and AI, and providing a strong technical voice in cross-functional discussions.
• Design, build, and deploy machine-learning pipelines for modeling jobseeker behavior and job marketplace dynamics.
• Monitor the performance of our models for speed and accuracy.

Minimum Qualifications:

• 6+ years of experience in a fast-paced software development environment at scale
• 2+ years of experience as a software engineering leader
• Proven experience either as an experienced Machine Learning manager or as a Senior/Staff Data Scientist or MLE looking to transition into management.
• Ability to assess technical value, speak the language of ML engineers, and evaluate if AI is being used effectively in day-to-day work.
• Strong communication skills to collaborate effectively with leadership, product, and data science teams.
• Deep experience with ML algorithms, techniques, and best practices.
• Strong CS fundamentals (data structures, algorithms) and coding skills.
• ML frameworks (TensorFlow, PyTorch, or scikit-learn)
• Python instead of R
• Java/Scala
• Applied experience with Embeddings and/or vectors (the focus is on applying proven techniques, using established tools, frameworks, and models) to solve real business problems efficiently.
• Demonstrated ability to build reproducible ML pipelines: including experiment tracking, data and model versioning, and environment management to ensure consistent, reliable results across runs and deployments.
• Have worked through multiple versions of the same product
• Experience working on a B2C or B2B Product

Preferred Qualifications:

• BS/MS/PhD in Mathematics, Computer Science, Physics, related technical field
• 3+ years of engineering management experience
• Demonstrated experience innovating novel approaches and solutions to ambiguous problems

As part of our team you’ll enjoy:

• Competitive compensation
• Exceptional benefits package
• Flexible Vacation & Paid Time Off
• Employer-matched 401(k) plan

The US base salary range for this full-time position is $200,000 - $265,000. Our salary ranges are determined by role, level, and location, and the range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location, role-related knowledge and skills, depth of experience, relevant education or training, and additional role-related considerations.

Depending on the position offered, equity, bonuses, commission, or other forms of compensation may also be provided as part of a total compensation package, in addition to a full range of medical, financial, and other benefits.