What will you do:
- Work in a collaboration of machine learning engineers and data scientists.
- Work on various disciplines of machine learning including but not limited to variety of disciplines includingdeep learning, reinforcement learning, computer vision, language, speech processingetc.
- Work closely with product management and design to define project scope, priorities and timelines.
- Work closely withmachine learning leadershipteam to define and implement thetechnology and architectural strategy.
- Take partialownership of project technical roadmap, which includes deciding, planning, publishing schedules, milestones, technical solution engineering, risks/mitigations, course corrections, trade-outs delivery.
- Deliver and maintainhigh-quality scalable systemsin a timely and cost-e ective manner.
- Recognising potential use-cases of cutting edge research inSprinklr productsand implementing your own solutions for the same.
- Stay updated on industry trends, emerging technologies, and advancements in data science, incorporating relevant innovations into the teams workflow.
What makes you qualified:
- Degree in Computer Science or related quantitative field of relevant experience from Tier 1 colleges.
- At least 5 years ofDeep Learning Experiencewith a distinguished track record on technically fast paced projects.
- Familiarity withcloud deployment technologies, such asKubernetes or Docker containers.
- Experience with large language models(GPT-3,4, Pathways, Google Bert, Transformer) and deep learningtools (TensorFlow, Torch).
- Working experience of software engineering best practices including coding standards, code reviews, SCM, CI, build processes, testing, and operations.
- Experience incommunicating with users, other technical teams, and product management to understand requirements, describesoftware product features, and technical designs.
Nice to have:
- Experience in directly managing a team of high calibre machine learning engineers and data scientists.
- Experience with Multi-Modal ML including Generative AI.
- Interested in and thoughtful about the impacts of AI technology.
- A real passion for AI!
