Lead ML Engineer — Recommendations & Retrieval (Remote)

Openkrill; United States; Hybrid; USD 205,000 - 265,000; Full time

Benefits offered by this job

Competitive compensation

Exceptional benefits package

Flexible Vacation & Paid Time Off

Employer‑matched 401(k) plan

Job summary

ZipRecruiter is seeking a Staff Machine Learning Engineer / Data Scientist to anchor its ML and AI initiatives, reporting to the Director of Recommendation Systems. You will shape a multi-year ML roadmap, craft core algorithmic architecture, and translate research into high-throughput production systems.

This role offers org-wide impact, mentoring for ML engineers, and establishment of best practices for model deployment and evaluation at scale.

Qualifications

• 8+ years of experience developing and deploying ML models in production.
• Proven track record architecting end-to-end ML solutions for production traffic at scale.
• Deep domain expertise in recommendation, personalization, ranking/retrieval, or interaction prediction.
• Strong software engineering fundamentals with hands-on experience in PyTorch or TensorFlow.
• Leadership and mentorship experience across cross-functional teams.
• Background in statistical modeling and online experimentation (A/B testing).

Responsibilities

• Define and execute the technical vision for core ML components in the marketplace.
• Architect high-scale ML systems for dynamic interaction prediction and candidate ranking.
• Solve two-sided marketplace matching and recommendation challenges in real time.
• Mentor ML Engineers and Data Scientists to promote best practices in model building and deployment.
• Oversee end-to-end model ownership from exploration to online evaluation and latency optimization.

Skills

Recommendation Systems

Personalization

Ranking & Retrieval

Interaction Prediction

Leadership

Education

MS/PhD in CS/ML or related field

Tools

PyTorch

TensorFlow

Job description

ZipRecruiter is seeking a Staff Machine Learning Engineer / Data Scientist to anchor its ML and AI initiatives, reporting to the Director of Recommendation Systems. You will shape a multi-year ML roadmap, craft core algorithmic architecture, and translate research into high-throughput production systems.

This role offers org-wide impact, mentoring for ML engineers, and establishment of best practices for model deployment and evaluation at scale.