Staff Machine Learning Engineer (Employer of Record)
Core
Design, build, and scale AI/ML and Generative AI solutions to solve complex business challenges and drive strategic goals for dealers, consumers, and operations.
Role type
Staff Machine Learning Engineer (Generative AI & Decision Science)
Builds
Enterprise-grade LLM-powered solutions, multi-agent GenAI systems, RAG pipelines, and scalable ML/AI infrastructure.
Domain
Used car finance / Automotive Finance / Generative AI
Deliverable
production ML models
Required skills
Decision science, machine learning, generative AI, large language models (LLMs), deep learning, graph neural networks, reinforcement learning, recommendation systems, transformers, causal inference, regression, parameter-efficient fine-tuning, model quantization, multi-agent system design, RAG pipeline engineering, microservices architecture (gRPC/GraphQL), ML lifecycle management, observability, automated training and monitoring.
Preferred skills
Automotive industry experience, model interpretability, responsible AI practices, advanced experimentation, visualization, Databricks ecosystem (MLflow, Model Serving), Apache Airflow, Spark, Flink, Kafka/Kinesis, Snowflake, multimodal AI, Chain-of-Thoughts/Tree-of-Thoughts prompting strategies.
Technologies
PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, Kubeflow, DVC, Ray, XGBoost, Causal Meta-Learner, LoRA, QLoRA, PEFT, gRPC, GraphQL, Databricks, Apache Airflow, Spark, Flink, Kafka, Kinesis, Snowflake
Responsibilities
Explore and apply advanced ML techniques including LLMs and graph neural networks to solve organizational challenges; define strategic roadmaps and translate them into actionable plans; design and deliver scalable, secure AI/ML systems; troubleshoot complex technical issues to improve system reliability; mentor data professionals on design principles and AI tools; architect and implement enterprise-grade LLM solutions managing the full lifecycle from requirements to production; design multi-agent GenAI systems and RAG pipelines; implement parameter-efficient fine-tuning strategies; build evaluation frameworks for LLM performance; integrate LLM solutions with enterprise architecture ensuring compliance.
Seniority
Staff, hands-on IC with strategic leadership and mentorship
