Machine Learning Engineer

Job Overview

We are seeking a highly skilled Machine Learning / Generative AI Engineer to join a team developing AI-powered solutions for a major financial services organization. The ideal candidate will have strong hands-on experience developing and deploying Machine Learning and Generative AI applications in production, along with expertise in Python, MLOps, AI validation, Responsible AI, and Model Risk Management.

This role will work closely with AI engineers, software developers, data teams, and Model Risk Management teams to build scalable, secure, reliable, and compliant AI solutions that meet enterprise SDLC and regulatory requirements.

Key Responsibilities

• Develop, test, validate, and deploy Machine Learning and Generative AI models in production environments.
• Build AI-powered applications using Python and other modern programming technologies.
• Design and maintain ML/AI pipelines and MLOps processes across the model lifecycle.
• Work with development and data teams to understand business problems, data sources, and existing systems and translate them into effective AI/ML solutions.
• Implement Responsible AI principles, including appropriate controls for fairness, transparency, explainability, privacy, and model safety.
• Partner with Model Risk Management (MRM) teams for model evaluation, validation, documentation, evidence gathering, and risk remediation.
• Establish and improve AI/ML governance frameworks covering development, validation, deployment, monitoring, and ongoing model management.
• Develop and integrate Generative AI/LLM solutions into enterprise applications.
• Implement testing and evaluation strategies to assess the quality, accuracy, reliability, and risks of AI-generated outputs.
• Containerize and deploy AI/ML applications using Docker/Kubernetes and cloud technologies.
• Follow enterprise SDLC, security, compliance, and regulatory requirements.
• Troubleshoot production issues and continuously improve the reliability, resiliency, and performance of AI solutions.
• Collaborate with cross-functional teams using Agile/DevOps methodologies.

Required Qualifications

• 4+ years of experience in Machine Learning, AI Engineering, Software Engineering, or a related field.
• Strong hands-on Python development experience.
• Experience developing and deploying Machine Learning models in production.
• Hands-on experience with Generative AI, LLMs, or AI-powered applications.
• Experience with MLOps, ML pipelines, model deployment, and model lifecycle management.
• Experience with Model Validation, Model Governance, or Model Risk Management (MRM).

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  Strong understanding of Responsible AI principles and AI validation/evaluation techniques.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Experience with Docker, Kubernetes, or containerized applications.
• Experience with software development lifecycle and enterprise production environments.
• Strong troubleshooting, analytical, communication, and problem-solving skills.

Preferred Qualifications

• Experience working in Banking, Financial Services, or another regulated industry.
• Experience with Claude Code, Codex, GitHub Copilot, or other AI-assisted development tools.
• Experience with Java and full-stack application development.
• Experience building RAG, LLM, or Agentic AI applications.
• Experience with AI/ML observability and monitoring.
• Experience establishing AI governance and MLOps frameworks.
• Experience with resiliency, automation, CI/CD, and DevOps practices.

Experience working in large enterprise environments