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Data & AnalyticsRemote

Senior Machine Learning Operations Engineer

Smartsheet · Remote

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Last seen by MeritLog September 8, 2026Source: GreenhouseSource version: greenhouse-job-board-v1

MeritLog read this listing from Smartsheet's Greenhouse job board and last checked it on September 8, 2026.

Source: the employer's Greenhouse job board. Open the original listing for current details.

Job details

Work model
Remote
Salary
Not listed by source
Location
Bangalore, INDIA

Hiring context

How this role compares at Smartsheet

Smartsheet has 90 live roles in MeritLog’s catalog across 9 job families, and 15 of them are in data & analytics. 0 of those listings publish a pay range, a disclosure rate of 0%.

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

What you'd do

  • Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices.
  • Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models.
  • Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models.
  • Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards.
  • Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation.
  • Incorporate user feedback for iterative improvements and manage necessary model retraining cycles.
  • Act as the "glue" between Data Scientists (who build models) and Software Engineers (who consume them).
  • Partner effectively with software engineers, product managers and business functions to integrate the machine learning solutions across smartsheet.
  • Provision and manage scalable cloud infrastructure using Infrastructure as Code (IaC).
  • Provide architectural guidance and mentorship to a team consisting of ML engineers, data scientists and analytics engineers.
  • Distill complex ML concepts into easy-to-follow technical documentation.
  • 5+ years of experience with creating, deploying and scaling machine learning solutions in a cloud environment (eg. AWS, GCP, Azure) and ability to use tools such as SageMaker, Glue, Lambda, Docker etc. to create ML models and data pipelines.
  • 7+ years of programming experience in languages used in AI/ML (eg python, scala etc)
  • 4+ years of experience in developing deep learning and traditional ML models using common frameworks like pytorch, tensorflow, huggingface, scikit-learn etc.
  • Strong applied data science skills - ability to recognize data patterns, understand how and when to use various machine learning approaches (eg. supervised/unsupervised learning, deep learning etc.), and evaluate the performance of ML algorithms.
  • Proven ability to remain up-to-date with the latest advancements in Generative AI approaches (eg. OpenAI, LangChain, Stable Diffusion APIs).
  • Experience developing, documenting, and supporting REST APIs
  • A degree in Computer Science, Engineering, or a related field or equivalent practical experience.

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

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. Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle. Your mission is to maintain and deploy ML models to a scalable, reliable, and secure production environment. You will design and maintain the infrastructure, automation, and monitoring systems that ensure our AI products are high-performing and cost-effective. You will report to our Director, Analytics Engineering & Data Governance and work from our Bangalore, India office. You Will: Model and Pipeline Automation • Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices. • Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models. • Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models. Governance & Compliance • Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards. Performance Monitoring • Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation. • Incorporate user feedback for iterative improvements and manage necessary model retraining cycles. Cross-Functional Collaboration • Act as the "glue" between Data Scientists (who build models) and Software Engineers (who consume them). • Partner effectively with software engineers, product managers and business functions to integrate the machine learning solutions across smartsheet. Architecture and Infrastructure Management • Provision and manage scalable cloud infrastructure using Infrastructure as Code (IaC). • Provide architectural guidance and mentorship to a team consisting of ML engineers, data scientists and analytics engineers. • Distill complex ML concepts into easy-to-follow technical documentation. You Have: • 5+ years of experience with creating, deploying and scaling machine learning solutions in a cloud environment (eg. AWS, GCP, Azure) and ability to use tools such as SageMaker, Glue, Lambda, Docker etc. to create ML models and data pipelines. • 7+ years of programming experience in languages used in AI/ML (eg python, scala etc) • 4+ years of experience in developing deep learning and traditional ML models using common frameworks like pytorch, tensorflow, huggingface, scikit-learn etc. • Strong applied data science skills - ability to recognize data patterns, understand how and when to use various machine learning approaches (eg. supervised/unsupervised learning, deep learning etc.), and evaluate the performance of ML algorithms. • Proven ability to remain up-to-date with the latest advancements in Generative AI approaches (eg. OpenAI, LangChain, Stable Diffusion APIs). • Experience developing, documenting, and supporting REST APIs • A degree in Computer Science, Engineering, or a related field or equivalent practical experience. Get to Know Us: 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. #LI-Remote

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