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Baton (A Ryder Technology Lab)

Software Engineer, MLOps - Machine Learning

Baton (A Ryder Technology Lab) · San Francisco, California, United States

Posted about 2 months ago · $162,000 - $216,000

or apply directly on Baton (A Ryder Technology Lab)'s site. We never take the application ourselves.

Is this posting real?

This role has been open
50 days
Baton (A Ryder Technology Lab)'s roles stay open a median of 51 days
Reposted
No
Salary listed
Yes
100% of Baton (A Ryder Technology Lab)'s roles list one
Ghost-job risk at Baton (A Ryder Technology Lab)
high
5 stale, 0 reposted of 8 open
Hiring momentum
9 roles opened in the last 90 days
↑ up vs. the prior 90 days
Last confirmed on the employer's board
2026-09-24

Measured from postings appearing on and disappearing from Baton (A Ryder Technology Lab)'s own greenhouse board since 2026-08-03. Full hiring picture for Baton (A Ryder Technology Lab).

About this role

As a Software Engineer in Baton’s Machine Learning Pod, you will be responsible for building and maintaining the production infrastructure that supports the machine-learning lifecycle. Your role involves automating model monitoring, retraining, and deployment, as well as enhancing integration between the ML platform and Baton’s core transportation management system. This hands-on position requires collaboration across software engineering and machine learning to ensure reliable and scalable operations.

Our read on this posting3.6out of 5
benefits
4/5
freshness
1/5
career value
4/5
role clarity
4/5
pay transparency
5/5

Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Baton (A Ryder Technology Lab) as an employer.

What you need

  • Production Python Expertise
  • Advanced proficiency coding in production-grade Python at an L4 or L5 level
  • Experience working in an environment where production code directly impacts operations
  • Ability to build and maintain reliable software across modeling, infrastructure, and automation workflows
  • Strong background in distributed computing, scalable ML infrastructure, and high-performance engineering
  • Experience building or maintaining systems that support data-intensive and ML workloads

Nice to have

  • Experience implementing, deploying, monitoring, and maintaining machine-learning models in production
  • Experience with Kubernetes and cloud infrastructure, preferably AWS
  • Familiarity with ML and data technologies such as Kubeflow, Iceberg, Feast, or SageMaker
  • Experience with batch prediction, model serving, distributed training, experiment tracking, caching, or feature stores
  • Experience building scalable, self-serving infrastructure for machine-learning teams

What you get

  • Competitive Base Salary + Cash Bonus Structure
  • Annual Company Bonus + Long Term Incentive Plan
  • 401(k) with Matching
  • Hybrid Work Schedule
  • Hyper-Stable, Publicly Traded Enterprise
  • Medical, Dental, and Vision Health Coverage

Worth weighing

  • No specific mention of the tech stack beyond Python and distributed systems
  • Role involves both infrastructure and modeling, which may require a broad skill set
  • The position is hybrid, requiring in-office presence three days a week
  • Experience with specific ML platforms like SageMaker is noted as a plus, not a requirement

Summarised from Baton (A Ryder Technology Lab)'s posting. Read the full original.

Listed by Baton (A Ryder Technology Lab) on their greenhouse job board, last confirmed open on 2026-09-24. PitchMeAI is not the employer.

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