Job Description
The Senior Machine Learning Engineer at Affinity is responsible for designing, developing, and deploying AI systems, particularly recommendation and ranking models, to extract insights from large datasets and enhance the company's relationship intelligence platform. The role involves collaborating with cross-functional teams to build scalable ML solutions that deliver actionable business insights.
Key Responsibilities
- Design, build, and deploy AI systems for extracting insights from business interaction data
- Own the full machine learning lifecycle from ideation to production, including feature engineering, model selection, deployment, and evaluation
- Translate business needs into robust machine learning solutions and system designs
- Develop recommendation and ranking systems using techniques like learn-to-rank, collaborative filtering, and hybrid search
- Work on information extraction, storage, and retrieval problems for structured and unstructured data
- Collaborate with cross-functional teams to build scalable data processing and ML operations systems
Requirements
- At least 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: Medical, dental, and vision insurance premiums covered with PPO, HDHP, and HMO options in CA, plus 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
Ready to Apply?
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