AI / ML Engineer

YOU ARE As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your role spans the full solution lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and DevOps & MLOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.

THE WORK

• Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions
• Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps & MLOps
• Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC
• Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites
• Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production
• Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools
• Justify the value of model approaches in business problems
• Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production

EDUCATION

• Bachelor's Degree or equivalent
• BASIC (REQUIRED) QUALIFICATION
• Proven experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.
• Proven experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming
• Proven experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks
• Proven experience in building and deploying AI/ML based software to a cloud environment.
• PREFERRED QUALIFICATION
• Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch)..
• Experience working with language models like LLM's APIs and optimizing their usage for specific applications.