Lead Product Engineer(Machine Learning)

Sprinklr is the definitive, AI-native platform for Unified Customer Experience Management (Unified-CXM), empowering brands to deliver extraordinary experiences at scale — across every customer touchpoint.

By combining human instinct with the speed and efficiency of AI, Sprinklr helps brands earn trust and loyalty through personalized, seamless, and efficient customer interactions. Sprinklr’s unified platform provides powerful solutions for every customer-facing team — spanning social media management, marketing, advertising, customer feedback, and omnichannel contact center management — enabling enterprises to unify data, break down silos, and act on real-time insights.

Today, 1,900+ enterprises and 60% of the Fortune 100 rely on Sprinklr to help them deliver consistent, trusted customer experiences worldwide.

Job Description 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.
• 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.

What makes you qualified:

• Degree in Computer Science or related quantitative field of 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-4, 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!

We focus on our mission : Sprinklr was founded in 2009 to solve a big problem: growing enterprise complexity that separated brands from their customers. Our vision was clear: to unify fragmented teams, tools and data — helping large organizations build deeper, more meaningful connections with the people they serve. Today, Sprinklr has a unified, AI-native platform for four product suites: Sprinklr Service, Sprinklr Social, Sprinklr Marketing, and Sprinklr Insights. Sprinklr is here to do three things:

• Lead a new category of enterprise software that we call Unified-CXM.
• Empower companies to deliver next generation, unified engagement journeys that reimagine the customer experience.
• Create a culture of customer obsession, with trust, teamwork, and accountability.

We believe in our product : Customers who value exceptional customer experiences have what they need on our single unified platform, built with an operating system approach on a single codebase. That means that everything — and everyone — can work together to service, respond, sell, and market to customers on the channels they prefer. While Unified Customer Experience Management (Unified-CXM) as a category is just getting started, we are well on our way to creating a no-compromise, unified approach to better customer experiences for the world’s leading enterprise brands.

We invest in our people : We offer a comprehensive suite of benefits designed to help each member of our team thrive. Sprinklr believes that you should be able to get the type of care you need for your personal well-being when you need it. We offer you and your family voluntary healthcare coverage in countries where applicable. We believe it is important to take time off – it is essential for your mental and physical wellbeing. We provide Sprinklrites with paid time off to recharge and spend time with loved ones. We want to grow our talent with purpose. Our open Mentoring Program is designed to create meaningful connections that support growth and amplify our focus.

To learn more about employee benefits by region, click here.

To learn more about all-things-Sprinklr, visit our candidate resource hub here.

EEO - Our philosophy : Our goal is to ensure every employee feels like they belong and are operating in a collaborative environment. We fervently believe every employee matters and should be respected and heard. We believe we are stronger when we belong because collectively, we’re more innovative, creative, and successful.

Sprinklr is proud to be an equal-opportunity workplace and complies with all applicable federal, state, and local fair employment practices laws. We are committed to equal employment opportunity regardless of race, color, religion, creed, national origin or ancestry, ethnicity, sex (including gender, pregnancy, sexual orientation, and gender identity), age, physical or mental disability, citizenship, past, current, or prospective service in the uniformed services, genetic information, or any other characteristic protected under applicable law.

Reasonable accommodations are available upon request during the interview process. To request an accommodation, please work directly with your recruitment coordinator or recruiter.

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