Engineering Manager, Machine Learning, Ranking
New
Z
ZipRecruiterOnline employment marketplace
Most US-based positions can also be performed remotelyFull-TimeManager
Salary200,000 - 265,000 USD per year
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Job Details
- Experience
- 6+ years of experience in a fast-paced software development environment at scale; 2+ years of experience as a software engineering leader; Preferred: 3+ years of engineering management experience
- Required Skills
- PythonJavaMachine LearningPyTorchTensorflowScalascikit-learn
Requirements
- Have 6+ years of experience in a fast-paced software development environment at scale.
- Have 2+ years of experience as a software engineering leader.
- Have experience as a Machine Learning manager or as a Senior/Staff Data Scientist or MLE transitioning into management.
- Be able to assess technical value, speak the language of ML engineers, and evaluate effective use of AI.
- Have deep experience with ML algorithms, techniques, and best practices.
- Have strong computer science fundamentals, including data structures and algorithms, and coding skills.
- Have experience with TensorFlow, PyTorch, or scikit-learn.
- Have Python skills; the posting specifies Python instead of R.
- Have Java or Scala skills.
- Have applied experience with embeddings and/or vectors to solve business problems.
- Have experience building reproducible ML pipelines, including experiment tracking, data and model versioning, and environment management.
- Have worked through multiple versions of the same product and have experience working on a B2C or B2B product.
Responsibilities
- Lead and support a senior team of Data Scientists, Generalists, and Machine Learning Engineers.
- Drive career development, workload balancing, and growth opportunities for the team.
- Partner with Product Management and Decision Science to shape the product roadmap.
- Define metrics and success criteria for marketplace balancing tests.
- Evaluate day-to-day technical work and ensure effective use of ML and AI.
- Provide a technical voice in cross-functional discussions.
- Design, build, and deploy machine-learning pipelines for modeling jobseeker behavior and job marketplace dynamics.
- Monitor model performance for speed and accuracy.
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