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Software Engineer - Training Infrastructure
Baseten · San Francisco · New York
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What Baseten asks for
From Baseten's Software Engineer - Training Infrastructure ad, checked 2 Nov 2026.
Go and distributed systems
At least 5 years of experience with software engineering, including proficiency in Go and a deep understanding of distributed systems and performance tuning.
Kubernetes and infrastructure design
Experience designing and architecting scalable infrastructure, with specific expertise using Kubernetes in production environments.
Observability systems
Evidence of designing observability systems to monitor workloads and ensure the reliability of technical systems.
ML and AI workloads
Experience working with machine learning and AI workloads or MLOps platforms.
Mentorship and technical leadership
Leading technical discussions and providing mentorship to more junior engineers regarding infrastructure best practices.
The ad asks for at least 5 years of experience and a bachelor's degree or higher in Computer Science or a related field. Listed in San Francisco and New York.
How the example answers the ad
Four of the five requirements above, each matched to a line in the example.
Kubernetes and infrastructure design
“Architected a new multi-tenant Kubernetes controller that increased model training throughput by 35 percent.”
Architecting a controller for Kubernetes in a production environment shows specific expertise in scalable infrastructure design.
ML and AI workloads
“Standardized internal MLOps deployment templates using Go to cut service onboarding time by 50 percent.”
Using Go to create standardized MLOps deployment templates provides evidence of working with machine learning and AI workloads.
Observability systems
“Integrated custom Prometheus exporters to track GPU utilization across 200 plus nodes in production.”
Using Prometheus exporters on 200 production nodes shows the design of observability systems to monitor specific hardware workloads.
Mentorship and technical leadership
“Mentored 3 junior engineers on distributed system debugging techniques and Go best practices.”
Advising 3 junior colleagues on debugging and coding standards shows mentorship regarding Go and infrastructure principles.
The whole example as text
Kwame Osei · Senior Software Engineer, Infrastructure
Summary
Software engineer with 6 years of experience specializing in high-throughput infrastructure and production-grade MLOps pipelines. Orchestrates distributed systems and Kubernetes clusters to support large-scale AI model training and serving workloads. Designs observability frameworks that reduce mean time to resolution for complex service failures by 40 percent. Mentors junior developers on system design principles and performance tuning to improve overall engineering velocity.
Experience
Senior Software Engineer, Infrastructure · Databricks
San Francisco, CA · 2025 - Present
- Architected a new multi-tenant Kubernetes controller that increased model training throughput by 35 percent.
- Integrated custom Prometheus exporters to track GPU utilization across 200 plus nodes in production.
- Standardized internal MLOps deployment templates using Go to cut service onboarding time by 50 percent.
- Led a task force of 5 engineers to optimize cluster scheduling, resulting in 25 percent lower cloud infrastructure costs.
- Facilitated weekly technical design reviews for cloud-native storage interfaces.
Software Engineer, Infrastructure · Stripe
South San Francisco, CA · 2023 - 2025
- Migrated legacy microservices to a service mesh architecture using Go, reducing service latency by 15 milliseconds.
- Designed and implemented a custom observability dashboard for monitoring high-throughput payment processing APIs.
- Managed a rolling upgrade of over 50 production Kubernetes clusters with zero downtime for external customers.
- Developed automated capacity planning tools that predicted infrastructure needs with 95 percent accuracy.
- Mentored 3 junior engineers on distributed system debugging techniques and Go best practices.
Software Engineer · HashiCorp
San Francisco, CA · 2021 - 2023
- Contributed to core Go-based infrastructure tooling used by over 5000 enterprise customers.
- Engineered a distributed configuration management subsystem that scaled to handle 10,000 requests per second.
- Decreased build and test cycle times by 40 percent through parallelization of CI pipelines.
- Collaborated with product teams to define technical roadmaps for next-generation secrets management features.
- Authored internal documentation on distributed tracing to standardize observability across the engineering organization.
Junior Site Reliability Engineer · Twilio
San Francisco, CA · 2020 - 2021
- Maintained fleet-wide Kubernetes infrastructure serving over 1 million API calls per hour.
- Wrote automation scripts in Python and Bash that reduced manual incident response tasks by 30 percent.
- Configured alerting policies in PagerDuty and Grafana to improve system reliability by 20 percent.
- Participated in on-call rotations for critical customer-facing messaging services.
- Assisted in the migration of on-premise monitoring tools to a cloud-based observability platform.
Education
Bachelor of Science in Computer Science · University of California, Berkeley
Berkeley, CA · 2016 - 2020
- Graduated with Honors in Computer Science with a 3.8 GPA.
- Completed thesis on distributed consensus algorithms in high-latency network environments.
- Served as a teaching assistant for the upper-division operating systems course.
Certificate in Cloud Architecture · Stanford University
Stanford, CA · 2020 - 2021
- Specialized in serverless computing and infrastructure as code methodologies.
- Developed a capstone project focused on multi-region Kubernetes cluster deployment automation.
- Awarded top performing project for cloud-native architectural design.
Skills
Frequently asked questions
Is the example from an employee?
No. It is an AI-written example for this ad, made to show how a resume can answer it.
What programming languages are preferred?
The ad requires proficiency in Go and mentions that experience with Python is a plus.
What specific AI frameworks are relevant to the role?
The role involves familiarity with the open source training stack and distributed training techniques, including tools like PyTorch, DeepSpeed, and FSDP.
Where do I apply?
On the official Baseten posting, through the job link on this page.
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