AI/ML Junior Computational Scientist

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 in Computer Science, Computer Engineering, Data Science, or a related field

Basic (required) Qualification

• Work or coursework experience with machine learning engineering or machine learning science, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.

• Experience (work or coursework) in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming

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.

• Experience with the following programming languages: Python, C++, Java, R, SQL

• Strong written &​ verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders

• Strong client-facing skillsets in a consulting environment

• Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams

• Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation