About the Company
Sprinklr is a leading enterprise software company for all customer-facing functions. With advanced AI, Sprinklr's unified customer experience management (Unified-CXM) platform helps companies deliver human experiences to every customer, every time, across any modern channel. Headquartered in New York City with employees around the world, Sprinklr works with more than 1,000 of the world’s most valuable enterprises — global brands like Microsoft, P&G, Samsung and more than 50% of the Fortune 100.
About the Role
In your role as a Lead Product Engineer, you will be tasked with creating and delivering novel machine learning solutions for next generation of digital customer experience applications.
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 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 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 solution engineering, risks/mitigations, course corrections, trade-outs, delivery.
- Deliver and maintain high-quality scalable systems in a timely and cost-effective manner.
- Recognizing 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.
What makes you qualified:
- Degree in Computer Science or related quantitative field of relevant experience from Tier 1 colleges.
- At least 3 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.
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!