Senior Machine Learning Engineer

About the role

Join Affinity, a leading relationship intelligence platform, as a Senior Machine Learning Engineer. In this role, you will collaborate with cross-functional teams to design and build AI systems that uncover insights from business interaction data. You will own the full ML lifecycle, translate business needs into ML solutions, and solve complex problems related to information extraction, storage, and retrieval. The position emphasizes engineering over research and offers a unique opportunity to advance ML engineering capabilities in the private capital CRM space. Key missions: Collaborate with cross-functional teams to design and build AI systems that uncover insights from business interaction data.. Own the full machine learning lifecycle, from ideation to production, including feature engineering, model selection, deployment, and model observability.. Architect and launch ranking and recommendation infrastructure from scratch, initially via integrated off-the-shelf models, and evolving to targeted and customized solutions. Profile: - 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. You may be just the right candidate for this or other roles - Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every qualification - Experience with serving ML models for streaming and batch inference at scale - Proficiency in Python and modern ML frameworks (PyTorch, Scikit-learn, or similar) - Track record of building maintainable, testable, and production-grade codebases - Experience with vector or graph databases - Hands-on experience developing ranking or recommendation systems from scratch, deployed at scale using techniques such as learn-to-rank, explainable recommendations - Experience with observability tools for online and offline model evaluation, A/B testing, and tracing for AI applications - 5+ years of experience in software engineering and/or Machine Learning experience in applying machine learning in production - Strong understanding of machine learning techniques, including clustering and decision trees - Experience with graph-based recommendation systems, such as graph NN - Experience with dataset engineering, including data curation, augmentation, and synthesis, to assist ML model improvement - Experience with packaging, CI/CD and pipeline automation