Description
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Job Description :
Responsibilities
- Own Core ML Infrastructure:
- Build and scale distributed systems for ML training, serving, and inference.
- Design and implement real-time ML workflows that power core product features.
- Implementation of Distributed Systems:
- Build robust distributed systems tailored for efficient ML training and seamless operational deployment.
- Feature Engineering Enhancement:
- Streamline and manage both online and offline feature stores, optimizing feature engineering processes for greater efficiency.
- Real-Time ML Workflow Enhancement:
- Improve real-time machine learning workflows to support dynamic decision-making and automate core operational processes.
- Platform Level Ownership:
- Lead the development of ML Ops systems, including model deployment, monitoring, and experiment tracking.
- Architect and manage scalable feature stores for online and offline usage.
- AI-Driven Optimization:
- Contribute to agentic AI systems for freight matching, ETA prediction, and load scheduling.
- Support systems that improve Stop Estimation Accuracy and Cross-Mode Optimization.
- Production Ready Engineering:
- Write production-grade Python that operates at scale, with reliability and performance top of mind.
- Collaborate across engineering and data science to turn models into resilient software systems.
Required Qualifications
- Production Python & Distributed Systems Expertise
- Advanced proficiency in Python at a Staff Level
- Must be within a production environment where the code directly impacts operations.
- Experience in distributed computing, scalable ML infrastructure, & high-performance engineering.
- Machine Learning (MLOps)
- Scales ML infra for multiple teams and use cases.
- Experience implementing and serving ML algorithms.
- Ensures reproducibility, lineage, and experiment rigor.
- Owns end-to-end ML systems: training, deployment, features, monitoring, rollback.
- Hands-on experience with data engineering, distributed training, model monitoring, and experiment tracking.
- Breadth of knowledge and applied experience across multiple ML applications, with proven ability to leverage a wide range of tools, frameworks, and systems.
- Technical Leadership & Cross-Functional Influence
- Leads design and delivery of large-scale ML or distributed systems.
- Defines reusable patterns, standards, and architectures.
- Drives decisions that improve reliability, latency, and developer velocity.
- Sets technical direction and elevates ML engineering standards.
- Communicates vision and trade-offs across disciplines.
- Can Mentor other ML engineers on the team.
Preferred Qualifications
- 5 to 8 years of backend or ML infrastructure experience.
- Proven track record building production ML workflows at scale.
- Experience in industry logistics, transportation, or freight is a bonus.
The Perks
- Competitive Base Salary
- Long Term Cash Incentive Plans
- Annual Company Bonus
- 401k with Matching
- Hybrid Work Schedule
- Comprehensive Health Coverage
- Hyper-Stable, publicly traded Enterprise
- Employee Stock Purchase Program (15% discount to market value)
- Collaborative, Tech-Forward, Cozy office environment in Hayes Valley
Compensation Range: The annual base salary range for this position is $250,000 - $330,000*
Compensation will vary based on factors including skill level, transferable knowledge, and experience.
Note that the above is not the representation of total compensation, which includes our LTI Package as well.
In addition to base salary, Baton's full-time employees are eligible for an annual company performance bonuses.
Job Category: Product Development
Compensation Information :
The compensation offered to a candidate may be influenced by a variety of factors, including the candidate's relevant experience; education, including relevant degrees or certifications; work location; market data/ranges; internal equity; internal salary ranges; etc. The position may also be eligible to receive an annual bonus, commission, and/or long-term incentive plan based on the level and/or type. Compensation ranges for the position are below:
Pay Type :
Salaried
Minimum Pay Range:
Maximum Pay Range:
Benefits Information:
For all Full-time positions only : Ryder offers comprehensive health and welfare benefits, to include medical, prescription, dental, vision, life insurance and disability insurance options, as well as paid time off for vacation, illness, bereavement, family and parental leave, and a tax-advantaged 401(k) retirement savings plan.
Ryder is proud to be an Equal Opportunity Employer and Drug Free workplace.
All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, age, status as a protected veteran, among other things, or status as a qualified individual with disability.
Important Note :
Some positions require additional screening that may include employment and education verification; motor vehicle records check and a road test; and/or badging or background requirements of the customer to which you are assigned.
Security Notice for Applicants:
Ryder will only communicate with an applicant directly from a [@ryder.com] email address and will never conduct an interview online through a chat type forum, messaging app (such as WhatsApp or Telegram), or via an online questionnaire. During an interview, Ryder will never ask for any form of payment or banking details and will never solicit personal information outside of the formal submitted application through www.ryder.com/careers .
Should you have any questions regarding the application process or to verify the legitimacy of an interview or Ryder representative, please contact Ryder at careers@ryder.com or 800-793-3754.
Current Employees :
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Job Seekers can review the Job Applicant Privacy Policy by clicking here (http://ryder.com/job-applicant-privacy-policy) .
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