TCS has always been in the spotlight for being adept in "the next big technologies". What we can offer you is a space to explore varied technologies and quench your techie soul.
Key Responsibilities
Collaborate with product managers, stakeholders, and engineering teams to define hypotheses and gather requirements.
Design, develop, and deploy robust, scalable machine learning models for production applications.
Research and integrate state-of-the-art GenAI models (e.g. GPT, T5, BERT, diffusion models, GANs) into business use cases.
Drive innovation in areas such as conversational AI, media synthesis, personalisation, and agentic systems.
Fine-tune and customise foundation models for specific domains and tasks.
Implement best practices for GenAI safety, alignment, and ethical deployment.
Stay current with GenAI research, open-source models, and industry trends.
Lead ML components from ideation to deployment, collaborating across distributed teams.
Design frameworks for agent development and cross-agent communication.
Collaborate with software engineers, data scientists, and product managers to define success metrics.
Review code, provide feedback, and mentor junior team members.
Communicate technical concepts and project updates to stakeholders across varying technical backgrounds.
Basic Qualifications
Minimum 10 years of experience in machine learning engineering or a related role.
Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers).
Experience with supervised fine-tuning (SFT), parameter-efficient fine-tuning (PEFT), model evaluation, and data preparation.
Strong understanding of MLOps, model monitoring, retraining, and guard railing.
Excellent written and verbal communication skills.
Ability to work independently and manage project-based goals across time zones.
Preferred Qualifications
Experience with agentic architectures and multi-agent systems.
Familiarity with GenAI safety frameworks and ethical deployment strategies.