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.
- 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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