Machine Learning / AI Contractor

Position Summary

Work you'll do

We’re seeking a Machine Learning / AI Contractor to build and operate production-grade AI solutions, including LLM-powered applications, predictive models, and optimization systems. The role requires strong Python and MLOps expertise, practical cloud and data-platform experience, and the ability to work effectively with senior technical and business stakeholders.

Key responsibilities

• Design, build, deploy, and maintain LLM-powered and agentic applications, including tracing, evaluation, and guardrails.
• Take predictive and optimization models from development through production; establish validation, monitoring, and retraining processes.
• Build and improve RAG solutions, including retrieval quality, embeddings, and vector-store integrations.
• Develop data pipelines and services using Python, SQL, and cloud-based data and ML platforms.
• Work with Kubernetes and AWS EKS, Databricks, SageMaker, and MLflow to support model development and deployment.
• Design data models and real-time processing solutions using SQL and NoSQL technologies.
• Collaborate with technical and business stakeholders to translate requirements into reliable AI/ML solutions.

Required qualifications

• MS in Computer Science, Statistics, Mathematics, Machine Learning, or a related field—or equivalent experience.
• At least 7 years of software development experience, including 4 or more years working on AI/ML solutions.
• Production experience with LLM-powered or agentic applications, including tracing, evaluations, and guardrails.
• Production experience with predictive or optimization models, including validation, monitoring, and retraining.
• Practical RAG experience, including retrieval quality, embeddings, and vector stores; Graph RAG experience is a plus.
• Advanced Python skills and strong knowledge of data structures, algorithms, machine learning, data mining, information retrieval, and statistics.
• Experience with Kubernetes, preferably AWS EKS.
• Experience training models in Databricks and SageMaker, and working with MLflow.
• Expert knowledge of at least one of AWS, Azure, or Kubernetes.
• Experience with data management, data-model design, and real-time processing using SQL (e.g., PostgreSQL) and NoSQL stores (e.g., OpenSearch, Redis).
• Strong communication skills and ability to partner with senior technical and business stakeholders.

Preferred qualifications

• Production experience with pricing, revenue management, elasticity, or demand-forecasting models.
• Experience with mathematical optimization, including linear and mixed-integer programming (e.g., OR-Tools or Gurobi), and constrained recommendation problems.
• Experience with causal inference, uplift modeling, or experiment design when randomization is limited.
• Experience delivering models through model risk management or an equivalent regulatory review.
• Financial-services or payments experience at a large institution, including Investment Banking, Markets, Securities Services, commercial cards, treasury services, or billing and revenue systems.
• Experience with agent frameworks or runtimes, A2A, or MCP.
• Experience designing agent memory and managing organizational context, including memory nodes and episodic or semantic memory.
• Experience with knowledge graphs and graph databases for retrieval.
• Understanding of LLM fine-tuning and small language model inference.
• Full-stack development experience with modern JavaScript/TypeScript frameworks (e.g., Next.js or Svelte) for agent UIs, including AG-UI or NEO UI SDK.
• Knowledge of high-performance languages such as Go or Rust.

About Deloitte