Baseten
Senior Software Engineer - Infrastructure
Baseten, San Francisco, California, United States, 94199
ABOUT BASETEN
Baseten powers inference for the world's most dynamic AI companies, like OpenEvidence, Clay, Mirage, Gamma, Sourcegraph, Writer, Abridge, Bland, and Zed. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting‑edge models into production. With our recent $150M Series D funding, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction, we’re scaling our team to meet accelerating customer demand.
THE ROLE As a Senior Infrastructure Software Engineer at Baseten, you’ll architect and lead development of our ML inference platform that powers production AI applications. You’ll make key technical decisions for the infrastructure enabling developers to deploy, scale, and monitor ML models with high performance and reliability.
EXAMPLE INITIATIVES You’ll get to work on these types of projects as part of our Infrastructure team:
Multi‑cloud capacity management
Inference on B200 GPUs
Multi‑node inference
Fractional H100 GPUs for efficient model serving
RESPONSIBILITIES
Design and architect scalable infrastructure systems for our ML inference platform
Lead optimization of Kubernetes deployments for efficient, cost‑effective model serving
Drive enhancements to our inference orchestration layer for complex model deployments
Define monitoring strategies for model performance, latency, and resource utilization
Develop advanced solutions for GPU capacity management and throughput optimization
Establish infrastructure automation standards to streamline ML deployment workflows
Partner with other engineers to translate complex inference requirements into technical solutions
Make critical architectural decisions balancing performance with system reliability
Lead technical discussions and mentor junior engineers on infrastructure best practices
Contribute to long‑term technical strategy and infrastructure roadmap
REQUIREMENTS
Bachelor’s degree or higher in Computer Science or related field
5+ years experience building production infrastructure systems
Expert‑level proficiency in Go, with Python experience a plus
Deep expertise with Kubernetes in production environments
Extensive experience with major cloud providers (AWS, GCP) and neo‑cloud providers (Crusoe, DigitalOcean, Nebius) a plus.
Advanced understanding of distributed systems concepts and performance tuning
Proven experience designing observability systems
Track record of leading technical initiatives and mentoring engineers
Experience with ML/AI workloads and MLOps platforms highly valued
BENEFITS
Competitive compensation package.
This is a unique opportunity to be part of a rapidly growing startup in one of the most exciting engineering fields of our era.
An inclusive and supportive work culture that fosters learning and growth.
Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now
to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
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THE ROLE As a Senior Infrastructure Software Engineer at Baseten, you’ll architect and lead development of our ML inference platform that powers production AI applications. You’ll make key technical decisions for the infrastructure enabling developers to deploy, scale, and monitor ML models with high performance and reliability.
EXAMPLE INITIATIVES You’ll get to work on these types of projects as part of our Infrastructure team:
Multi‑cloud capacity management
Inference on B200 GPUs
Multi‑node inference
Fractional H100 GPUs for efficient model serving
RESPONSIBILITIES
Design and architect scalable infrastructure systems for our ML inference platform
Lead optimization of Kubernetes deployments for efficient, cost‑effective model serving
Drive enhancements to our inference orchestration layer for complex model deployments
Define monitoring strategies for model performance, latency, and resource utilization
Develop advanced solutions for GPU capacity management and throughput optimization
Establish infrastructure automation standards to streamline ML deployment workflows
Partner with other engineers to translate complex inference requirements into technical solutions
Make critical architectural decisions balancing performance with system reliability
Lead technical discussions and mentor junior engineers on infrastructure best practices
Contribute to long‑term technical strategy and infrastructure roadmap
REQUIREMENTS
Bachelor’s degree or higher in Computer Science or related field
5+ years experience building production infrastructure systems
Expert‑level proficiency in Go, with Python experience a plus
Deep expertise with Kubernetes in production environments
Extensive experience with major cloud providers (AWS, GCP) and neo‑cloud providers (Crusoe, DigitalOcean, Nebius) a plus.
Advanced understanding of distributed systems concepts and performance tuning
Proven experience designing observability systems
Track record of leading technical initiatives and mentoring engineers
Experience with ML/AI workloads and MLOps platforms highly valued
BENEFITS
Competitive compensation package.
This is a unique opportunity to be part of a rapidly growing startup in one of the most exciting engineering fields of our era.
An inclusive and supportive work culture that fosters learning and growth.
Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now
to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
#J-18808-Ljbffr