Senior ML/AI Engineer #3624294

About the role

Join a mission-driven technology organization focused on improving aging and long-term care experiences by building modern digital solutions. The environment is collaborative, product-focused, and purpose-driven.

Responsibilities

• Design, build, train, evaluate, and deploy ML models for predictive analytics, classification, NLP, anomaly detection, generative AI, etc.
• Develop production-ready AI/ML solutions on Databricks Lakehouse using Python, Spark, MLflow, Delta Lake.
• Build automated, reproducible feature pipelines, training workflows, and model refresh cycles.
• Own end-to-end ML lifecycle: experimentation, model registry, deployment, monitoring, drift detection, optimization.
• Design modular ML architectures integrating with APIs, data warehouses, microservices, downstream applications.
• Develop LLM-powered applications with prompt engineering, RAG systems, embeddings, vector search.
• Partner with data engineering, product, platform, business stakeholders to turn ambiguous opportunities into measurable outcomes.
• Support A/B testing, offline/online evaluation, statistical validation, clear communication of results.
• Document models, systems, workflows for cross-team adoption.

Qualifications

• Required: 7+ years in ML, AI, ML engineering, or similar hands-on role.
• Strong expertise in Python, Spark, Databricks, MLflow, SQL, large-scale distributed datasets.
• Experience building, deploying, and monitoring ML models in production.
• Strong understanding of supervised/unsupervised learning, deep learning, transformers, embeddings, vector stores, LLM systems.
• Experience with reproducible ML pipelines, CI/CD, model deployment, observability.
• Solid software engineering foundation (version control, testing, modular architecture, reliability).
• Ability to communicate technical concepts to non-technical stakeholders and influence direction.
• Experience in agile product environments with cross-functional teams.
• Nice to have: Databricks Model Serving, Unity Catalog, Feature Store, Delta Live Tables, RAG systems, LLM fine-tuning, model distillation, AWS, Azure, Kubernetes, containers, real-time ML, streaming data, event-driven architectures.

Benefits

• Comprehensive benefits, retirement savings, generous PTO, paid holidays, paid family leave, wellness support, tuition reimbursement, student loan repayment, training/certification support.

Pay

Not specified

Schedule

Not specified

Skills

Not specified

Benefits

• Comprehensive benefits, retirement savings, generous PTO, paid holidays, paid family leave, wellness support, tuition reimbursement, student loan repayment, training/certification support.

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