Senior MLOps Engineer

At Navan, "It's all about the user. All of them." We're passionate about providing a seamless one-stop experience for business travelers, no matter how they travel, where they stay, or where they're going.

Navan is looking for a Senior MLOps Engineer with strong machine learning skills to join our growing team. You will work within our world-class data organization to help modernize and scale our ML platform, powering our data-driven company and supporting our rapidly evolving machine learning needs. You'll have the opportunity to improve our existing ML infrastructure and to design, build and maintain ML deployment processes and pipelines. The ideal candidate will be extremely curious and will use their ML skills and business mindset to make a difference every day. We are looking for people who can thrive in a fast-paced environment by dealing with multiple moving pieces while still maintaining quality, long-term thinking, and delivering value to our customers. We take great pride in our diversity of backgrounds, cultures, and perspectives and we strongly believe this is helping us to grow as a successful and impactful team.

To learn more about how Navan is leading with AI/ML, follow the links below for some of the articles published by Ilan Twig, Navan CTO

• How an AI Language Model Manipulated Me In Order to Avoid Failure
• Maximizing the Potential of Generative AI
• Why AI Will Go Big By Thinking Small

What You'll Do:

• Design, implement, and optimize MLOps architectures to support Navan's machine learning initiatives
• Work closely with data science, product, and engineering teams to develop and deploy advanced ML models, including recommendation systems and rankers
• Develop, productize and maintain ML pipelines for model training, evaluation,  deployment
• Design and Implement best practices for model versioning, experimentation, and reproducibility
• Continuously improve our ML infrastructure for stability, scalability, observability, and security
• Develop internal tooling and libraries to enhance ML workflow efficiency
• Review and manage user access, creating documentation for best practices

What We're Looking For:

• BS or MS in Computer Science, Engineering, Mathematics, or related technical field
• 3+ years of relevant work experience in Machine Learning Engineering or MLOps
• Strong proficiency in Python and Terraform
• Hands-on expertise and experience in deploying models via AWS SageMaker, AWS Bedrock, including open source LLM models
• Hands-on experience with evaluating and selecting LLMs for business problems
• Deep knowledge of AWS core services (EC2/ECS, RDS, S3, Lambda, API Gateway etc.)
• Hands-on experience with CI/CD pipeline implementation using tools like GitHub (Workflows and Actions), Docker, Jenkins, Blue Ocean
• Strong understanding of MLOps best practices and tools 
• Hands-on experience with model monitoring, drift detection, and automated retraining processes
• Familiarity with containerization and orchestration technologies (Docker, AWS Fargate, Kubernetes)
• Strong understanding of recommendation systems and ranking algorithms
• Experience with ML online experimentation frameworks and A/B testing
• Solid foundation in probability and statistics
• Familiarity with Snowflake for data storage and processing
• Strong problem-solving skills and ability to work in a fast-paced, collaborative environment

The posted pay range represents the anticipated low and high end of the compensation for this position and is subject to change based on business need. To determine a successful candidate’s starting pay, we carefully consider a variety of factors, including primary work location, an evaluation of the candidate’s skills and experience, market demands, and internal parity.

For roles with on-target-earnings (OTE), the pay range includes both base salary and target incentive compensation. Target incentive compensation for some roles may include a ramping draw period. Compensation is higher for those who exceed targets. Candidates may receive more information from the recruiter.