Data Scientist

About the Role

We are looking for an experienced Data Scientist with strong hands-on expertise in

Machine Learning, Deep Learning, GenAI, NLP, and Computer Vision. The ideal candidate will work on building, fine-tuning, deploying, and optimizing AI/ML solutions, including

LLM-based applications, AI agents, RAG pipelines, and computer vision models.

You will work closely with engineering and cross-functional teams to take AI solutions from experimentation to production.

Key Responsibilities

• Design, develop, train, and optimize Machine Learning and Deep Learning models.
• Work with large-scale image, video, and text datasets, including data preprocessing and augmentation.
• Develop solutions using Python, PyTorch, TensorFlow, and other modern ML frameworks.
• Work with Transformers, RNNs, Transfer Learning, Vision Transformers (ViT), and fine-tuning techniques.
• Build and optimize NLP and Generative AI solutions.
• Develop RAG pipelines, agentic workflows, and AI agents using frameworks such as

LangGraph.

• Design and optimize prompt engineering workflows for LLMs such as GPT, Claude, and LLaMA.
• Implement and optimize Computer Vision models, including CNN-based architectures and modern vision models.
• Apply MLOps best practices, including model versioning, CI/CD, automated deployment, monitoring, and model lifecycle management.
• Collaborate with engineering teams to productionize AI/ML models and applications.
• Follow enterprise-level AI security, governance, compliance, and software development best practices.
• Analyze model performance and continuously improve accuracy, scalability, and efficiency.

Required Skills

• 4+ years of hands-on experience in Data Science / Machine Learning / AI.
• Strong programming skills in Python.
• Hands-on experience with PyTorch and/or TensorFlow.
• Strong understanding of Machine Learning and Deep Learning concepts.
• Experience with NLP, Transformers, LLMs, and Generative AI.
• Experience building RAG pipelines and agentic AI workflows.
• Hands-on experience with AI Agent frameworks, preferably LangGraph.
• Experience with prompt engineering and LLM fine-tuning.
• Strong understanding of Computer Vision, image/video processing, and deep learning architectures.
• Experience with MLOps, model deployment, versioning, and CI/CD pipelines.
• Strong knowledge of data preprocessing, feature engineering, model evaluation, and optimization.
• Experience working with Databricks and Azure.
• Good understanding of Linux/UNIX environments and command-line tools.
• Understanding of enterprise AI security, governance, and compliance.

Good to Have

• Experience with CNNs, Reinforcement Learning, and Vision Transformers (ViT).
• Experience working with multimodal AI models.
• Experience with model optimization and inference performance.
• Experience with cloud-based AI/ML platforms.
• Experience mentoring junior Data Scientists or ML Engineers.