ML Ops Consultant (Intermediate)

Roles: ML Ops Consultant

Location:  Jersey City, NJ (5 days)

Duration: 6+ Months

Required Qualifications, Capabilities, and Skills

• MS in Computer Science, Statistics, Mathematics, Machine Learning, or related field (or equivalent experience).
• Minimum 5+ years of development experience, with at least 4 years working on AI/ML solutions.
• Hands-on experience building LLM-powered or agentic applications in production, including tracing, evaluations, and guardrails.
• Hands-on experience taking predictive or optimization models to production and keeping them healthy there, including validation, monitoring, and retraining.
• Practical RAG experience — retrieval quality, embeddings, and vector stores; Graph RAG a strong plus.
• Strong programming skills in Python, with deep knowledge of data structures, algorithms, machine learning, data mining, information retrieval, and statistics.
• Knowledge of Kubernetes (AWS EKS).
• Experience with training models in Databricks and SageMaker.
• Experience working with MLflow.
• Expert knowledge of at least one of: AWS, Azure, Kubernetes.
• Knowledge of data management and data model design; real-time processing using both SQL (e.g., Postgres) and NoSQL stores (e.g., OpenSearch, Redis).
• Excellent communication skills with the ability to partner effectively with senior technical and business stakeholders.

Preferred Qualifications, Capabilities, and Skills

• Experience with pricing, revenue management, elasticity, or demand forecasting models in a production setting.
• Experience with mathematical optimization (linear and mixed-integer programming, e.g., OR-Tools or Gurobi) and with constrained recommendation problems.
• Experience with causal inference, uplift modelling, or experiment design where randomization is limited.
• Experience delivering models through model risk management or equivalent regulatory review.
• Experience working in the financial or payments domain at a large institution (Investment Banking, Markets, Securities Services, or adjacent), or with commercial card, treasury services, or billing and revenue systems.
• Experience with agent frameworks or runtimes, A2A, or MCP.
• Agent memory design (memory nodes, episodic/semantic memory) and organizational context management.
• Knowledge graphs and graph databases used for retrieval.
• Understanding of LLM fine-tuning and small language model inference.
• Ability to develop full-stack products using modern JavaScript/TypeScript frameworks (e.g., Next.js, Svelte) for agent UIs (AG-UI / NEO UI SDK).