Senior Machine Learning Operations Engineer

Smartsheet

United States

Remote

USD 47,000 - 78,000

Full time

14 days+
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Job summary

Smartsheet is seeking a Senior Machine Learning Operations Engineer to architect our ML production lifecycle. You will maintain, deploy, and scale models in a secure, cost‑effective production environment, building CI/CD/CT pipelines and IaC-based infrastructure.

You will collaborate with data scientists and software engineers, guide ML tooling decisions, and mentor a team of ML engineers and analytics professionals from our Bangalore office.

Qualifications

  • 5+ years in cloud ML deployment and scaling.
  • 7+ years programming in Python/Scala.
  • 4+ years building DL and ML models with common frameworks.
  • Strong applied data science and pattern recognition.
  • Experience with Generative AI approaches and APIs.

Responsibilities

  • Automate ML model deployment and retraining pipelines.
  • Architect scalable, secure production ML infrastructure.
  • Collaborate with data scientists and software engineers.
  • Mentor ML engineers and analytics professionals.

Skills

ML Ops
Python/Scala
DL/ML frameworks
Applied data science
Generative AI
REST APIs
Cloud platforms

Education

Bachelor's degree in CS/Engineering

Tools

SageMaker
Glue
Lambda
Docker
AWS/GCP/Azure

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.

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