Senior Machine Learning Engineer, AI Insights
Employment Information
Job Description
Senior Machine Learning Engineer designing and building AI systems for Affinity's relationship intelligence platform. Collaborating with cross-functional teams to shape the future of private capital's CRM platform.
Responsibilities:
- Own the full ML lifecycle: Take projects from ideation to production, including feature engineering, model selection, deployment, and model observability and evaluation.
- Translate business needs into ML solutions: Gather product requirements and translate them into robust ML system design requirements.
- Build sophisticated recommendation and ranking systems: Design and implement ranking and recommendation systems using techniques such as learn-to-rank (LTR) and collaborative filtering.
- Solve complex problems: Work on a variety of information extraction, information storage and information retrieval problems for both structured and unstructured data.
- Collaborate cross-functionally: Partner with cross-functional teams (product management, infrastructure, data engineering, and software engineering) to build robust, high-scale systems that underlie all of our data processing and ML Operations.
Requirements:
- 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
- Collaborative filtering and content-based filtering
- Reranking strategies and hybrid search implementations
- Information retrieval and relevance scoring
- Solid understanding of machine learning techniques, including clustering and decision forests.
- Experiences with serving ML models for streaming and batch inference at scale.
- Experience with vector databases (milvus, weaviate) or graph database (Neo4j)
- Proficiency in Python and modern ML frameworks (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, A/B testing, and tracing for AI applications.
- Nice to Have:
- Experience with dataset engineering, including data curation, augmentation, and synthesis, to assist ML model improvement.
- Develop AI applications powered by LLMs and agent-based systems
- Familiar with modern LLM development frameworks:
- Feature development: LangChain, LlamaIndex, or similar orchestration frameworks
- Evaluation & monitoring: LangSmith, Weights & Biases, TruLens, DeepEval, Azure AI, or equivalent tools
- Experience with text-to-SQL (text2sql) generation or similar natural language to structured query tasks
- Experience with packaging, CI/CD and pipeline automation.
Benefits:
- Health Benefits: We cover your medical, dental, and vision insurance premiums with comprehensive PPO, HDHP and HMO options (in CA), and offer flexible personal & sick days to support your well-being.
- Retirement Planning: We offer a 401(k) plan to help you plan for your future.
- Learning & Development: We provide an annual education budget and a comprehensive L&D program.
- Wellness Support: We reimburse monthly for things like home internet, meals, and wellness memberships/equipment to support your overall health and happiness.
- Team Connection: Virtual team-building activities and socials to keep our team connected, because building strong relationships is key to success.
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