Senior Machine Learning Engineer II
Build and operate low-latency machine learning systems for ad ranking, relevance, and optimization, including feature pipelines, experimentation, evaluation, and production inference. The role requires 6+ years of software engineering experience, strong Python skills, AWS experience, and practical LLM application experience.
About the job
Responsibilities
- Design, build, and improve machine learning models for ad ranking, relevance, and optimization.
- Implement active learning strategies, including data sampling, error-driven retraining, and human-in-the-loop workflows.
- Use LLMs for synthetic data generation, assisted labeling, weak supervision, and ranking/relevance error analysis.
- Own ML experimentation, offline and online evaluation, and production inference for ad-ranking components.
- Partner with product, data, and platform teams to translate advertiser and user-experience gaps into measurable improvements.
- Maintain model performance, reliability, latency, and data quality in production ranking systems.
- Use AI-assisted tools for development, experimentation, debugging, analysis, prototyping, and design validation.
Requirements
- 6+ years of software engineering experience building and maintaining production ML or data-driven systems.
- Strong Python proficiency for machine learning and data processing; working knowledge of Go.
- Experience deploying low-latency models into production ranking or decisioning systems.
- Experience with AWS and distributed systems, including scalable training pipelines and online inference services.
- Practical experience applying LLMs to model development and data-labeling workflows.
- Strong engineering judgment and systems mindset, emphasizing reliability, performance, and maintainability.
- Experience with AI-assisted development tools such as GitHub Copilot or ChatGPT.
- Ability to evaluate AI-generated outputs, debug complex issues, and validate correctness in production ML workflows.
Nice-to-haves
- Bachelor’s or master’s degree in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
- Familiarity with AWS Bedrock, LangChain, vector databases, or similar orchestration technologies.
- Experience operating LLM workflows, prompt-driven systems, and model-assisted pipelines.
- Experience orchestrating ML-driven decisions in high-throughput or low-latency ranking, recommendation, or optimization environments.
- Applied machine learning experience in relevance, ranking, or personalization, including feature engineering, model evaluation, and feedback loops.
- Experience working in small, fast-moving, cross-functional teams.
Compensation and Benefits
- Base salary: $211,353–$248,650.
- Equity for full-time employees.
- 401(k) match up to 4%.
- Medical, dental, and vision plans, including pet coverage.
- Up to $10,000 per year in education reimbursement.
- Employee resource groups.
Skills
Python, Go, AWS, Distributed Systems, Machine Learning, LLMs, Active Learning, Synthetic Data Generation, Weak Supervision, Model Evaluation, Online Inference, Ranking Systems, LangChain, Aws Bedrock, Vector Databases
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