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Senior Lead Product Engineer

Senior Lead Product Engineer

ConfidentialGurgaon / Gurugram, India
9 days ago
Job description

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.

Job Description

Role : In your role as a Senior Lead Product Engineer(Machine Learning) with us , 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.
  • 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 6 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!
  • Why You'll Love Sprinklr :

    We're committed to creating a culture where you feel like you belong, are happier today than you were yesterday, and your contributions matter. At Sprinklr, we passionately, genuinely care. For full-time employees, we provide a range of comprehensive health plans, leading well-being programs, and financial protection for you and your family through a range of global and localized plans throughout the world.

    For more information on Sprinklr Benefits around the world, head to https : / / sprinklrbenefits.com / to browse our country-specific benefits guides.

    We focus on our mission : We founded Sprinklr with one mission : to enable every organization on the planet to make their customers happier. Our vision is to be the world's most loved enterprise software company, ever.

    We believe in our product : Sprinklr was built from the ground up to enable a brand's digital transformation. Its platform provides every customer-facing team with the ability to reach, engage, and listen to customers around the world. At Sprinklr, we have many of the world's largest brands as our clients, and our employees have the opportunity to work closely alongside them.

    We invest in our people : At Sprinklr, we believe every human has the potential to be amazing. We empower each Sprinklrite in the journey toward achieving their personal and professional best. For wellbeing, this includes daily meditation breaks and virtual fitness. We have continuous learning opportunities available with LinkedIn Learning and more.

    EEO - Our philosophy : Our goal is to ensure every employee feels like they belong and are operating in a judgment-free zone regardless of gender, race, ethnicity, age, and lifestyle preference, among others. We value and celebrate diversity and 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 is an affirmative-action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. See also Sprinklr's EEO Policy and EEO is the Law.

    Warning about Recruiting Scams :

    Please be vigilant for recruiting scams impersonating Sprinklr. Sprinklr will never ask you for money, to pay for equipment, or for unnecessary personal information during the interview process. Sprinklr will also never pay in Bitcoin or send email communications from our executives. Please review the Federal Trade Commission's advice to avoid these types of scams.

    If you are contacted by someone whom you suspect may not be appropriately representing Sprinklr, please do not engage and block their email or phone number immediately.

    Skills Required

    Transformer, Machine Learning, reinforcement learning, Speech Processing, Deep Learning, Tensorflow, Docker, Kubernetes, Computer Vision

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