Affinity stitches together billions of data points from massive datasets to create a powerful, accurate representation of the world's professional relationship graph. Based on this data, we offer our users the insights and visibility they need to nurture and tap into the opportunities in their team's network. The AI Insights team owns the services that power Affinity's industry-leading relationship intelligence platform. We extract and retrieve information from billions of structured and unstructured data points to deliver actionable insights to customers.
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
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.
Other
- Studies have shown that women and people of color are less likely to apply to jobs unless they meet every qualification. At Affinity, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role, but your past experience doesn’t perfectly align with the qualifications above, we encourage you to apply anyways.
- We iterate quickly. As such, you must be comfortable embracing ambiguity, be able to cut through it, and deliver value to our customers.
- We are candid, transparent, and speak our minds while simultaneously caring personally with each person we interact with.
- We make data-driven decisions and make the best decision for the moment based on the information available.
- We use E-Verify
