Responsibilities :
- Lead the design, development, and deployment of advanced machine learning models and algorithms for various applications.
- Perform comprehensive data analysis, feature engineering, and model training with large and complex datasets.
- Collaborate with cross-functional teams to understand business requirements and translate them into sophisticated technical solutions.
- Architect and deploy scalable AI / ML models, including large language models (LLMs) and transformer-based architectures.
- Implement MLOps best practices for CI / CD, automated model retraining, and lifecycle management.
- Optimize AI / ML pipelines for distributed computing, leveraging cloud platforms and
accelerators (GPUs / TPUs).
Develop and maintain scalable advanced AI solutions such as retrieval-augmented generation (RAG) and fine-tuning techniques (LoRA, PEFT).Conduct thorough model evaluation, validation, and testing to ensure high performance and accuracy.Stay at the forefront of AI / ML advancements and integrate cutting-edge techniques into existing and new projects.Mentor and provide technical guidance to junior developers and team members.Author and maintain detailed documentation of processes, methodologies, and best practices.Implement and optimize cutting-edge deep learning models, such as Generative Adversarial Networks (GANs) and transformer architectures (e.g., BERT, GPT).Explore and implement federated learning approaches to build AI / ML models while preserving patient data privacy and security.Integrate explainable AI (XAI) techniques to ensure transparency and interpretability of machine learning models.Translate complex AI concepts into actionable insights for business stakeholders.Required Qualifications :
Bachelor's, Master's in Computer Science, AI, ML, Data Science, or related fields.7+ years of experience with AI / ML solutionsExtensive experience in developing and deploying machine learning models in a productionenvironment.
Expertise in Python (NumPy, Pandas, scikit-learn), and proficiency in Java, Scala, or similarlanguages.
Deep understanding of deep learning frameworks (TensorFlow, PyTorch, JAX) and NLP libraries (Hugging Face Transformers).Hands-on experience with MLOps, including containerization (Docker, Kubernetes), CI / CD, and model monitoring.Well versed with Agentic AI.Deep understanding on Langchain ecosystem.Experience with distributed computing (Apache Spark, Ray) and large-scale dataset processing.Proficiency in vector databases (FAISS, Chroma DB, Pinecone) for efficient similarity search.Strong expertise in fine-tuning transformer models, hyperparameter optimization, andreinforcement learning.
In-depth experience with cloud platforms such as AWS, Azure, or Google Cloud for deploying AI solutions.Strong analytical, problem-solving, and communication skills to bridge technical and business perspectives.Preferred Qualifications :
Experience in regulated industries such as healthcare, biopharma.Contributions to AI research, open-source projects, or top-tier AI conferences.Familiarity with generative AI, prompt engineering, and advanced AI topics like graph neural networks.Proven ability to scale AI teams and lead complex AI projects in high-growth environments(ref : hirist.tech)