Senior AI/ML Engineer

Job Description

JPMorgan Chase is hiring a senior AI/ML Engineer to join a technology team building and operating machine learning and AI systems inside a large financial services environment. This role sits onsite in Jersey City, NJ or Plano, TX and works closely with data science, platform engineering, and product partners to take models from design through production. 10 or more years of software engineering experience is required, with significant hands on machine learning or AI engineering work. Strong programming skills in Python are required; additional experience in Java or Scala is a plus. Candidates should have hands on experience with at least one ML framework such as TensorFlow, PyTorch, or scikit learn, and experience building and operating ML pipelines in a cloud environment such as AWS, Azure, or GCP. The interview process includes a live coding round, so solid grounding in data structures, algorithms, and system design is expected, along with experience in SQL and large scale data processing tools such as Spark or Kafka. A bachelor's degree in Computer Science, Engineering, or a related field is required. Prior experience in financial services or another regulated industry is preferred, as is exposure to MLOps tooling, large language models, prompt engineering, or model governance processes common in banking. This is a W2 contract engagement. Work authorization is limited to US Citizens, Green Card holders, or TN visa holders (Canada); no C2C and no H1B sponsorship or transfer.

Responsibilities

• Design, build, and maintain machine learning and AI models supporting core business functions
• Partner with data scientists and engineers to turn model prototypes into production services
• Own the full model lifecycle: data preparation, training, evaluation, deployment, and monitoring
• Build and maintain data pipelines that feed model training and inference
• Participate in code review and hold the team to consistent engineering standards
• Troubleshoot model performance issues in production and drive fixes
• Explain technical tradeoffs and results clearly to technical and non technical stakeholders
• Mentor junior engineers on ML engineering practices

Technologies & Skills

Benefits

• Opportunity to work on production AI/ML systems at scale within one of the world's largest financial services firms
• Direct hands-on technical work without unnecessary overhead; your time is engineering time
• Exposure to cutting-edge ML and AI technologies in a regulated, high-stakes environment
• Competitive hourly rate and focused engagement aligned with your technical expertise
• Ability to build significant portfolio work and credibility on real systems that millions of customers depend on
• Collaborative environment with senior engineers and data scientists across distributed teams