For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day.
Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.
You Will:
You Have:
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At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.
Equal Opportunity Employer:
Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, India, and Singapore. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.
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Build and improve the model-training pipeline and infrastructure, from cluster scheduling and reinforcement-learning code execution to evaluation throughput, while strengthening software quality and enabling faster model experimentation.
Own and optimize GPU infrastructure for LLM training and production serving, operating distributed clusters and improving workload throughput, latency, reliability, and cost through profiling and acceleration.
Build and operate distributed infrastructure for large-scale LLM training, reinforcement learning, and inference, improving researcher iteration speed, GPU utilization, system performance, and training reliability.
Lead the development and deployment of production-grade machine learning systems, shaping architecture and engineering standards while advising clients and mentoring engineers.
Lead the design and production deployment of agentic AI systems, translating advances in LLM research into scalable, secure clinical applications and guiding evaluation, data, and engineering practices.
