AI/ML Engineer

Overview

Design, develop, and implement AI/ML solutions for business problems, taking projects from proof of concept and pilot through production deployment in healthcare and other regulated environments.

What you'll do

• Design, develop, and implement AI/ML solutions to solve business problems, contributing to projects from proof of concept and pilot through production deployment.
• Build and apply traditional machine learning models and modern AI techniques, including large language models (LLMs), generative AI, retrieval-augmented generation (RAG), and agentic AI systems.
• Collaborate with senior engineers, product managers, data scientists, and business stakeholders to refine project scope, technical approach, success metrics, and deployment requirements.
• Contribute to scalable and maintainable AI systems focused on accuracy, robustness, fairness, and explainability while adhering to responsible AI principles.
• Apply model evaluation frameworks to assess performance, generalization, bias, and resilience to edge cases or adversarial inputs.
• Support the transition of AI prototypes into production-ready systems by partnering with platform and engineering teams on deployment, monitoring, and lifecycle management.
• Contribute to documentation, governance, and compliance processes to meet enterprise and regulatory standards, especially in healthcare and other regulated environments.

What you'll need

• Bachelor’s Degree or higher in Computer Science, Data Science, Engineering, Mathematics, or a related technical field, and 5-10 years of job-related experience.
• Proficiency in AI programming languages, such as Python.
• Hands-on experience with ML libraries and frameworks such as PyTorch, TensorFlow, scikit-learn, AWS Bedrock, and Azure AI Foundry.
• Solid software engineering skills, including testing, code quality, modular design, and performance awareness.
• Experience building end-to-end ML pipelines, including data preparation, training, evaluation, and deployment integration.
• Experience designing, training, and tuning deep neural networks.
• Understanding of model architecture, training dynamics, and evaluation techniques.
• Exposure to autonomous and/or multi-agent systems, including basic agent orchestration and tool usage.
• Understanding of reliability, safety, and evaluation considerations for agent-based systems.
• Familiarity with deploying or supporting AI solutions on cloud platforms.
• Professional proficiency in English.

Nice to have

• Master’s degree or higher in Computer Science, Machine Learning, AI, or a related field.
• Exposure to regulated industries such as healthcare, with understanding of compliance and governance requirements.
• Enthusiasm for solving complex AI problems and a strong desire for continuous learning and innovation.

Details

• Work location: Hybrid.
• Location: Bangalore, India.
• Domestic travel may include up to 20%.
• You may be required to enter healthcare or other third-party facilities.
• Healthcare or other third-party facilities may require certain licenses, vaccinations, and/or other credentials or qualifications as prerequisites to entry.