Affinity - Senior Machine Learning Engineer

• 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. 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. • 5+ years of experience in software engineering and/or Machine Learning experience in applying machine learning in production. • Hands-on experience developing ranking or recommendation systems from scratch, deployed at scale using techniques such as learn-to-rank, explainable recommendations • Strong understanding of machine learning techniques, including clustering and decision trees • Experience with serving ML models for streaming and batch inference at scale. • Experience with vector or graph databases. • 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. • Experience with dataset engineering, including data curation, augmentation, and synthesis, to assist ML model improvement. • Experience with graph-based recommendation systems, such as graph NN. • Experience with packaging, CI/CD and pipeline automation. • Tech stack: Our ML pipeline manages multiple Python services that support various AI features, including utilizing OCR to extract information from unstructured data, serving embedding models to vectorize chunks, and ranking a list of recommendations based on relevance and user preference. • Our culture is a key part of how we operate, as well as our hiring process: • 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. • If you’d like to learn more about our values, click here. • Work Location: San Francisco, New York, or US Remote (Affinity is registered to employ in certain U.S. states) • For those located in San Francisco or New York, for this role we're embracing a hub-hybrid model, designed to balance flexibility with meaningful in-person collaboration. Team members within commuting distance are expected in-office 2 days per week, typically Tuesday through Thursday. We believe great things happen when people come together intentionally to connect, create, and build momentum as a team. • What you'll enjoy at Affinity: • We live our values: As owners, we take pride in everything we do. We embrace a growth mindset, engage in respectful candor, act as playmakers, and "taste the soup" by diving deep into experiences to create the best outcomes for our colleagues and clients. • 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. • Please note that the role compensation details below reflect the base salary only and do not include any equity or benefits. This represents the salary range that Affinity believes, in good faith, at the time of this posting, that it will pay for the posted job. • A reasonable estimate of the current range is $160,000 to $235,000 USD. Within the range, individual pay depends on various factors including geographical location and review of experience, knowledge, skills, abilities of the applicant.