Senior ML/AI Engineer

Salary: $141000 - 274000 per year Requirements: We look for 7+ years of experience in machine learning, applied AI, or a similar engineering discipline. We need strong hands-on expertise with Python, Spark, Databricks, and MLflow for building ML solutions. We expect deep familiarity with modern machine learning methods, including supervised and unsupervised learning, deep learning, transformers, embeddings, vector stores, and LLM-based systems. We value a solid grasp of software engineering practices such as version control, testing, CI/CD, observability, and modular architecture. We need experience deploying machine learning models into production with dependable pipelines and monitoring. We look for the ability to explain complex technical ideas clearly to non-technical stakeholders. We prefer experience working in agile product environments. We require proficiency in SQL and experience handling large-scale distributed datasets. Nice-to-have experience includes Databricks Model Serving, Unity Catalog, Feature Store, and Delta Live Tables. Additional desirable experience includes building LLM-powered applications, retrieval-augmented generation systems, fine-tuning, or model distillation. Familiarity with AWS or Azure, Kubernetes, and container orchestration is a plus. A background in statistics, computer science, machine learning engineering, or a related field is advantageous. We especially value interest in building foundational ML platforms, tools, and frameworks for internal teams. Experience with real-time ML systems, streaming data, or event-driven architectures is also beneficial. Responsibilities: We design, build, evaluate, and deploy machine learning models for prediction, classification, NLP, anomaly detection, and generative AI use cases. We apply modern ML methods, experimentation approaches, and statistical best practices to improve accuracy, fairness, and reliability. We develop LLM-enabled applications, prompt engineering strategies, and retrieval-augmented generation systems where relevant. We create scalable features using Delta Lake, Spark, and Databricks Feature Store. We partner with data engineering teams to assess data availability, quality, lineage, and ingestion patterns. We build automated, reproducible pipelines that support training, validation, and model refresh cycles. We own the end-to-end ML lifecycle using Databricks workflows, MLflow, feature stores, and model registries. We develop CI/CD and automated deployment pipelines that support strong performance and reliability. We implement monitoring for drift, model degradation, data quality issues, and performance regressions. We design modular, scalable ML architectures that integrate with APIs, data warehouses, microservices, and downstream applications. We determine whether classical ML, deep learning, or LLM-based methods best fit business constraints. We build A/B tests, offline and online evaluation frameworks, and statistical validation strategies. We analyze model outcomes and communicate insights clearly to both technical and non-technical partners. We collaborate with product, engineering, and business teams to identify ML opportunities, refine requirements, and deliver measurable impact. We participate in architecture reviews, technical planning sessions, and roadmap discussions. We document our work in a way that is scalable and easy for future engineers to adopt. We stay current with emerging ML frameworks, LLM advances, Databricks capabilities, and scalable architecture patterns. We explore new tools, libraries, and platforms that can improve model performance or development efficiency. Technologies: AI AWS Azure CI/CD Databricks Support Kubernetes LLM Machine Learning Python SQL Spark Unity microservices Cloud GameDev More: We are CareScout, a wholly owned subsidiary of Cobalt Streamworks Financial, Inc., and we are on a mission to simplify and dignify the aging experience. We are building a new experience for care seekers and their families by bringing long-term care options, non-healthcare resources, education, and human support together in one place. Our team is curious, collaborative, and deeply committed to belonging, and we live by four values: make it human, make it about others, make it happen, and make it better. This Senior ML/AI Engineer role is available in Richmond, VA on a hybrid basis or remotely for candidates in approved Eastern Time locations. We offer a competitive compensation range, bonus eligibility, and a broad benefits package that includes healthcare, retirement savings, paid time off, family leave, wellness support, tuition reimbursement, and caregiver and mental health resources. last updated 26 week of 2026