AI Team Lead

Project description

We're seeking an AI Engineer to design, build, and deploy production-grade ML/AI systems. You'll work with product, data and infrastructure teams to convert research and models into scalable, maintainable services that deliver real business value for one of the biggest financial institutions in USA. Compensation USD Gross per year, based on your experience and interview results.

• Design, develop and deploy ML/AI models and pipelines for production use.
• Collaborate with data engineers to build robust data collection, validation, and feature pipelines.
• Implement model training, evaluation, versioning, and monitoring workflows (CI/CD for ML).
• Optimize models and inference for latency, throughput, cost, and accuracy.
• Build APIs, microservices or serverless components to serve models in production.
• Implement observability: metrics, logging, model drift detection, and alerting.
• Conduct A/B tests and performance analysis; iterate on models based on real-world feedback.
• Ensure model reproducibility, documentation and compliance with data privacy and security requirements.
• Mentor junior engineers and contribute to engineering best practices.

• BS/MS in Computer Science, Engineering, Statistics, or related field (or equivalent experience).Capital Markets experience
• 2+ years of experience building and deploying ML/AI systems in production.
• Experience with LLMs, embeddings, retrieval-augmented generation (RAG) and MCP.
• Experience with MLOps tools and workflows (MLflow, Kubeflow, TFX or similar).
• Experience deploying models with cloud platforms (AWS/GCP/Azure) and container orchestration (Docker, Kubernetes).
• Solid software engineering fundamentals: APIs, testing, CI/CD and code review.
• Familiarity with model evaluation metrics, validation techniques, and bias/fairness considerations.
• Strong communication skills and ability to work cross-functionally.

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