Job Description

Key Responsibilities:

Identify, define, and deliver AI/ML and GenAI use cases in collaboration with business and technical stakeholders Design, develop, and deploy models using Google Cloud's Vertex AI platform Fine-tune and evaluate Large Language Models (LLMs) for domain-specific applications Ensure responsible AI practices and governance in solution delivery Collaborate with data engineers and architects to ensure robust and scalable pipelines Document workflows and experiments for reproducibility and handover readiness Apply strong knowledge in supervised, unsupervised, and reinforcement learning Utilize Vertex AI features including AutoML, Pipelines, Model Registry, and Generative AI Studio Work on GenAI workflows: prompt engineering, fine-tuning, and model evaluation Develop in Python using ML frameworks like TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers Communicate and collaborate across product, data, and business teams

Required Skills:

Hands-on experience with Vertex AI on GCP - model training, deployment, endpoint management, MLOps Practical knowledge of PaLM, Gemini, or other LLMs via Vertex AI or open-source Proficiency in Python for ML pipeline scripting, data preprocessing, and evaluation Expertise in ML/GenAI libraries: scikit-learn, TensorFlow, PyTorch, Hugging Face, LangChain Exposure to CI/CD for ML, containerization using Docker/Kubernetes Familiarity with GCP services like BigQuery, Cloud Functions, Cloud Storage Experience with media datasets and real-world ML applications in OTT, DTH, Web platforms

Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related fields 3+ years of hands-on experience in ML/AI or GenAI projects * Any relevant certifications in ML, GCP, or GenAI technologies are a plus