About the job
Affinity integrates billions of data points from extensive datasets to craft a precise and powerful depiction of the global professional relationship graph. Our users gain essential insights and visibility to cultivate and leverage opportunities within their teams' networks.
The position is part of the AI Platform team, responsible for the AI services that drive Affinity's premier relationship intelligence platform. Our work involves extracting and retrieving information from vast amounts of structured and unstructured data to provide actionable insights to our clients.
As a Senior Machine Learning Engineer, you'll collaborate closely with data engineers, software engineers, and product managers to shape the future of the leading CRM platform in private capital. Your role will involve designing and building AI systems that efficiently uncover insights from dynamic business interaction data—an exciting and unique opportunity within the sector.
This position focuses on applied machine learning with a significant emphasis on engineering rather than research. You will be instrumental in enhancing our ML Engineering capabilities, specifically in information retrieval and ultimately in recommendation systems.
Key Responsibilities:
- Own the full ML lifecycle: Guide projects from ideation to production, encompassing feature engineering, model selection, deployment, and model observability and evaluation.
- Translate business needs into ML solutions: Gather product requirements and convert them into robust ML system design specifications.
- Build recommendation and ranking systems: Architect and implement ranking and recommendation infrastructure from the ground up, initially leveraging integrated off-the-shelf models and evolving to tailored solutions over time.
- Solve complex problems: Tackle diverse challenges in information extraction, storage, and retrieval for both structured and unstructured data.
- Collaborate cross-functionally: Work alongside cross-functional teams (product, infrastructure, data engineering, and software engineering) to develop robust, high-scale systems that underpin our data processing and ML operations.

