- Work on various disciplines of machine learning, including but not limited to a variety of disciplines, including deep learning, reinforcement learning, computer vision, language, speech processing, etc.

- Work closely with product management and design to define project scope, priorities and timelines.

- Work closely with the machine learning leadership team to define and implement the technology and architectural strategy.

- Take partial ownership of the project technical roadmap, which includes deciding, planning, publishing schedules, milestones, technical solution engineering, risks/mitigations, course corrections, trade-offs, and delivery.

- Deliver and maintain high-quality, scalable systems in a timely and cost-effective manner, recognising potential use-cases of cutting-edge research in Sprinklr products and implementing your own solutions for the same.

- Stay updated on industry trends, emerging technologies, and advancements in data science, incorporating relevant innovations into the team's workflow.

Requirements :

- Degree in Computer Science or a related quantitative field, or relevant experience from Tier 1 colleges.

- At least 5 years of Deep Learning Experience with a distinguished track record on technically fast-paced projects.

- Familiarity with cloud deployment technologies, such as Kubernetes or Docker containers.

- Experience with large language models (GPT-3 Pathways, Google Bert, Transformer) and deep learning tools (TensorFlow, Torch).

- Working experience of software engineering best practices, including coding standards, code reviews, SCM, CI, build processes, testing, and operations

- Experience in communicating with users, other technical teams, and product management to understand requirements, describe software product features, and technical designs.