Job
Description
In this role at GlobalLogic, you will take a lead position in solving complex real-world challenges across diverse domains by designing, developing, and deploying transformative AI solutions. You will have the opportunity to own internal AI product development, guide client-facing initiatives, and shape the technical direction of AI capabilities. This is an ideal position for a hands-on practitioner and strategic thinker who thrives in dynamic environments and is passionate about advancing the state of AI. **Key Responsibilities:** - Lead the end-to-end design, development, and deployment of cutting-edge NLP and Generative AI systems using Large Language Models (LLMs) to address business-critical challenges. - Research and implement state-of-the-art AI techniques, including RAG architectures, fine-tuning (PEFT, LoRA), Agentic AI systems, and multi-modal models. - Architect and maintain robust, production-grade pipelines for model training, deployment, monitoring, and automated retraining ensuring system reliability and efficiency. - Identify and mitigate issues such as hallucination, bias, and latency. Develop and enforce guardrails, observability metrics, and safety protocols to ensure fair, reliable, and compliant AI solutions. - Optimize inference performance through quantization, model distillation, and efficient pipeline design to reduce latency and operational costs. - Partner with cross-functional teams, clients, and stakeholders to define requirements, translate business needs into technical deliverables, and deliver tailored AI-powered solutions. - Mentor junior data scientists, promote best practices in AI/ML development, and contribute to a culture of continuous innovation and learning. **Qualification Required:** - 4+ years of hands-on experience in Data Science, AI/ML, or related fields, with a proven record of delivering production-grade NLP and Generative AI solutions. - Deep understanding of transformer-based architectures (e.g., BERT, GPT, LLaMA, Mistral) and hands-on experience with advanced fine-tuning methods such as PEFT, LoRA, and prompt engineering. - Strong expertise in designing and implementing Retrieval-Augmented Generation (RAG) systems using vector databases like Pinecone, Chroma, FAISS, or similar. - Expert-level skills in Python and major ML libraries such as PyTorch, TensorFlow, Hugging Face, and Scikit-learn. Familiarity with backend frameworks (e.g., Flask, Django) for API development is highly desirable. - Practical experience applying MLOps principles, including containerization (Docker, Kubernetes), CI/CD automation, and deploying scalable AI systems on AWS, GCP, or Azure. - Strong problem-solving, analytical, and research abilities, with the capacity to work independently, manage multiple priorities, and deliver innovative solutions in ambiguous environments. - Must possess any graduation degree (Must have Provisional Certificate & Consolidated Marks Memo). - Must be willing to work from office & in rotational shifts (5 Working Days & 2 Week Offs). - Must be ready to join immediately.,
