Machine Learning Engineer

Posted Yesterday
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Palo Alto, CA
Hybrid
160K-280K Annually
3-5 Years Experience
Fintech • Information Technology • Payments • Productivity • Software • Travel • Automation
Travel & expense made easy.
The Role
As a Machine Learning Engineer at Navan, you will enhance the ML infrastructure, design and implement MLOps architectures, and collaborate with teams to deploy ML models. You will also focus on optimizing ML pipelines, best practices for model management, and improving workflow efficiency within a fast-paced environment.
Summary Generated by Built In

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 Machine Learning Engineer with strong MLOps 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.

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.

Pay Range

$159,750$280,000 USD

Top Skills

Python

What the Team is Saying

Anna
Roshni
Brian
 Adamas Victória
Jordan
The Company
HQ: Palo Alto, CA
3,000 Employees
Hybrid Workplace
Year Founded: 2015

What We Do

Navan is the all-in-one super app that makes travel and expense easy so you can focus on being there, not getting there. Say goodbye to spending hours on the phone trying to change your flight or saving stacks of receipts to manually input expenses. From EAs and finance teams to travel managers and employees, Navan empowers people to focus on the things that matter most to them — all while providing companies with real-time visibility, savings, and control.

Navan’s investors include visionaries like Andreessen Horowitz, Lightspeed Ventures, Greenoaks, Zeev Ventures, and entrepreneurs Lee Fixel, Adam Bain, and Elad Gil. In Oct 2022, Navan announced its Series G upround at a post-money valuation of $9.2B to help accelerate future growth plans.

In April 2023, Navan expanded in the Indian market with the acquisition of Tripeur, a modern, people-centric corporate travel and expense management company. The group’s fifth acquisition in under two years, Tripeur joined the Navan Group alongside Spanish meetings and events specialists, Atlanta Events & Corporate Travel Consultants; Berlin-based modern travel management company, Comtravo; leading Scandinavian travel agency Resia AB; and London-based high-touch TMC, Reed & Mackay.

Why Work With Us

At Navan, we’re never satisfied with the status quo, and we know breakthrough ideas come from diverse perspectives. We are committed to cultivating a workplace that reflects the diversity of the customers we serve while fostering leadership and innovation.

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Navan Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

In-person connections is the foundation of Navan, the connections forged through face-to-face interactions improve company culture and what we can achieve together. We operate on a hybrid working model, which we define as three days a week in-office.

Typical time on-site: 3 days a week
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