AI Research Scientist

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We are seeking a highly skilled

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• Research, design, and implement novel AI/ML algorithms and optimization frameworks.
  
• Develop and deploy solutions in domains such as language models, computer vision, signal processing, generative AI, agentic AI, and digital twins.
  
• Apply advanced mathematical programming and optimization techniques to real-world business problems.
  
• Work with graph theory, knowledge graphs, and large-scale data architectures (Neo4j, cuGraph).
  
• Build, train, and optimize models using deep learning frameworks (PyTorch, TensorFlow).
  
• Leverage GPU-accelerated computing (CUDA, Rapids, NeMo, NIM) for high-performance AI solutions.
  
• Collaborate with cross-functional teams including researchers, engineers, and business stakeholders.
  
• Document research findings, contribute to publications, and share results through technical reports or academic papers.
  
• Ensure responsible AI practices including fairness, interpretability, and ethical AI usage.
  

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• PhD in Computer Science, Applied Mathematics, Engineering, or related field with focus on AI/Optimization.
  
• 3–5 years of applied AI research and deployment experience.
  
• Strong foundation in linear algebra, probability, stochastic processes, and optimization theory.
  
• Expertise in algorithm design, linear/non-linear programming, convex optimization, or combinatorial methods.
  
• Hands-on experience with neural networks, transformers, diffusion models, or generative modeling.
  
• Skilled in Python and C++ programming (CUDA experience is a plus).
  
• Strong knowledge of AI frameworks and libraries (PyTorch, TensorFlow).
  
• Familiarity with GPU accelerated computing, version control, and containerization (Docker, Kubernetes).
  
• Excellent problem-solving, analytical, and communication skills.
  

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• Experience in regulated industries (finance, healthcare, insurance).
  
• Knowledge of Big Data technologies (Spark, Kafka, Redis, Elastic Search).
  
• Proficiency in distributed training, hyperparameter optimization, and workflow automation (GitHub Actions, Terraform, Helm).
  
• Strong in microservices, APIs, and large-scale real-time AI systems.
  
• Contributions to open-source AI projects, research publications, or conference presentations.
  
• Familiarity with Responsible AI practices and fairness auditing.