About the Role
As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients. Your role involves combining custom models with cloud and third-party AI services to deliver production-ready outcomes. You will manage the full solution lifecycle, from assessing client needs and data to model selection and customization (including Deep Learning, Generative AI, and Large Language Models), to designing scalable data and DevOps & MLOps pipelines for training and production, ensuring the quality, value, and reliability of deployed systems.
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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 business needs, data availability, and system and infrastructure requirements, including edge devices and high-performance computing (HPC).
- Engage in research and development of new AI and high-performance compute algorithms, models, and simulations 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, including deploying models in production at scale and managing monitoring, alerting, automatic bug filing, and auditing.
- Experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming.
- Hands-on experience in distributed computing systems and architectures, including big data, high-performance computation, engineering simulations, scientific computing, grid and cloud computing, and distributed networks.
- Experience in building and deploying AI/ML-based software to a cloud environment.
Preferred Qualification
- Proficiency in Python and python-based AI/ML frameworks along with 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 programming languages such as Python, C++, Java, R, and SQL.
- Strong written and verbal communication skills with the ability to convey complex technical concepts to non-technical stakeholders.
- Strong client-facing skills in a consulting environment.
- Strong cross-functional skills with the ability to collaborate with various internal and client-side teams.
- An entrepreneurial mindset with curiosity and passion for emerging technologies and driving innovation.
- An MS or PhD in a related field (computer science, engineering, etc.) is preferred.
