Lead Product Engineer - Machine Learning

Responsibilities:
Work in a collabora on of machine learning engineers and data scientists.
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 milestones.
Work closely with the machine learning leadership team to define and implement the technology and architectural strategy.
Take partial ownership of project technical roadmap, which includes deciding, planning, publishing schedules, milestones, technical solutions on engineering, risks/mi ga ons, course corrections, trade-offs, and delivery.
Deliver and maintain high-quality, scalable systems in a timely and cost-effective manner.
Recognizing poten al 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 related quantitative field with 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 soware 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 soware product features, and technical designs.

Experience
4-8 yrs