Job Description
A Senior Machine Learning Engineer at Affinity is responsible for designing, developing, and deploying scalable AI systems, particularly recommendation and ranking models, to extract insights from large datasets and support the company's relationship intelligence platform. The role involves full ML lifecycle ownership, cross-functional collaboration, and applying machine learning techniques to solve complex information retrieval and extraction problems.
Key Responsibilities
- Design, build, and deploy AI systems for extracting insights from business interaction data
- Develop and implement recommendation and ranking systems using techniques like learn-to-rank and collaborative filtering
- Manage the full machine learning lifecycle from feature engineering to model evaluation and deployment
- Translate business needs into robust machine learning solutions and system designs
- Collaborate with cross-functional teams to build scalable data processing and ML operations systems
- Work on information extraction, storage, and retrieval problems for structured and unstructured data
Requirements
- Minimum of 5 years of experience in software engineering and/or Machine Learning experience in applying machine learning in production.
- Hands-on experience developing recommendation and ranking systems at scale, using techniques such as Learn-to-rank (LTR) algorithms, including RankNet, LambdaRank, or similar approaches.
- Experience with collaborative filtering and content-based filtering, reranking strategies, and hybrid search implementations.
- Solid understanding of machine learning techniques, including clustering and decision forests.
- Experience with serving ML models for streaming and batch inference at scale.
- Experience with vector databases such as Milvus, Weaviate, or graph databases like Neo4j.
- Proficiency in Python and modern ML frameworks such as PyTorch, Scikit-learn, or similar.
- Track record of building maintainable, testable, and production-grade codebases.
- Experience with observability tools for online and offline model evaluation, including A/B testing and tracing for AI applications.
Benefits & Perks
Health Benefits: coverage for medical, dental, and vision insurance premiums with comprehensive PPO, HDHP, and HMO options in CA, and flexible personal sick days
Retirement Planning: 401(k) plan
Learning Development: annual education budget and comprehensive learning and development program
Wellness Support: monthly reimbursements for home internet, meals, wellness memberships, and equipment
Team Connection: virtual team-building activities and socials
Salary Range: $106,200 to $210,000 USD (base salary, excluding equity and other benefits)
Ready to Apply?
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