Who you are

• 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
• 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

What the job involves

• This role is part of the AI Insights team, which owns the services that power Affinity's leading relationship intelligence, which is achieved through information retrieval from billions of unstructured and structured data points
• As a Senior Machine Learning Engineer, you will collaborate with data engineers, software engineers, and product managers to shape the future of private capital's leading CRM platform
• In this role, you will design and build AI systems that efficiently uncover insights from compelling business interaction data – an exciting and unique opportunity within the industry
• This is an applied machine learning position with a strong emphasis on engineering, not research. You will play a key role in advancing our ML Ops and ML Engineering capabilities
• 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
• 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. We maintain the Docker images and deployment pipeline via CircleCI. Our data stack includes Spark, Python, Kafka, and Databricks

Benefits

• Daily lunches
• Commuter passes
• Flexible PTO
• Free events
• Tech pack
• Retirement options
• Work from home opportunities
• Health insurance
• Grocery allowance