Job Description
<h3>📋 Description</h3> •Take projects from ideation to production, including feature engineering, model selection, deployment, and model observability and evaluation.
•Gather product requirements and translate them into robust ML system design requirements.
•Work on a variety of information extraction, information storage and information retrieval problems from both structured and unstructured data sources.
•Architect efficient and scalable systems to support serving inference services.
•Develop reusable AI-based services — including ML models, foundation models, and agents — that will be consumed by other backend services at Affinity.
•Lead complex technical initiatives and provide technical input for peers through system design reviews, code reviews, and promoting best practices.
•Collaborate with cross-functional teams (product, infra, data engineer, and software engineer) and ML engineering teams to build robust, high-scale systems that underlie all of our data processing and ML Operations. <h3>🎯 Requirements</h3> •5+ years of experience in software engineering and/or Machine Learning experience in applying machine learning in production, with a focus on ML Engineering and ML Ops.
•Experience in the following technical areas:
•Architecture design for distributed systems.
•Building maintainable and testable codebases and services.
•Developing ML systems, such as recommendation systems and information retrieval solutions.
•Relational DB, non-relational DB, and vectorDB.
•Developing AI applications powered by LLMs and/or agents.
•Proficient in building services in Python and common ML frameworks, such as PyTorch and Scikit-learn.
•Experience with observability tools for both online and offline evaluation and tracing for AI applications.
•Demonstrated experience working with large datasets, and are comfortable with high-scale data ingestion, transformation, analysis, and prediction tools.
•Experience working collaboratively with engineering, product, data, and other cross-functional teams.
•Nice to Have:
•Experience with developing machine learning applications at scale, from inception to driving user impact.
•Familiar with serving machine learning models for streaming and batch inference at scale.
•Experience with packaging, CI/CD and pipeline automation.
•Good understanding of machine learning systems’ testing, benchmarking, and online monitoring.
•Experience with dataset engineering, including data curation, augmentation, and synthesis, to assist ML model improvement. <h3>🏖️ Benefits</h3> •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.