Job Description
A Senior Machine Learning Engineer at Affinity is responsible for designing, developing, and deploying AI systems that extract insights from large-scale structured and unstructured data, focusing on recommendation and ranking systems to enhance the company's relationship intelligence platform.
Key Responsibilities
- Own the full machine learning lifecycle from ideation to production, including feature engineering, model deployment, and evaluation.
- Translate business needs into robust machine learning system designs.
- Build and deploy recommendation and ranking systems, developing infrastructure from scratch and evolving to customized solutions.
- Work on information extraction, storage, and retrieval problems for structured and unstructured data.
- Collaborate with cross-functional teams to build scalable data processing and ML operations systems.
Requirements
- At least 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 and 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 such as 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.
Benefits & Perks
Salary range of $160,000 to $235,000 USD, depending on experience and location
Work location options include San Francisco, New York, or US Remote with a hybrid model in SF and NY
Health insurance coverage for medical, dental, and vision with PPO, HDHP, and HMO options
Flexible personal sick days
Retirement plan with a 401(k)
Annual education budget and comprehensive learning and development program
Wellness support including monthly reimbursements for home internet, meals, and wellness memberships
Virtual team-building activities and socials
Ready to Apply?
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