Senior Infrastructure Software Engineer

San Francisco Bay Area

Baseten

Effortlessly serve optimized open source & custom models on the fastest, most reliable model delivery network

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ABOUT BASETEN

Join our dynamic team at Baseten, where we’re revolutionizing AI deployment with cutting-edge inference infrastructure. Backed by premier investors such as IVPSpark CapitalGreylock, and Conviction, we’re trusted by leading enterprises and AI-driven innovators—including DescriptBland.aiPatreonWriter, and Robust Intelligence—to deliver top-tier performance, security, and reliability for their production workloads. With our recent $75 million Series C funding, we’re poised to accelerate our mission to make AI accessible across all products. If you’re passionate about tackling impactful challenges and building transformative solutions from the ground up, we invite you to join us on this exciting journey!

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.

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 (Unlimited PTO, 401k, covered healthcare premiums, remote-first culture).

  • 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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Category: Engineering Jobs

Tags: AWS Computer Science Distributed Systems Engineering GCP GPU Kubernetes Machine Learning ML models MLOps Python Security Spark

Perks/benefits: Career development Competitive pay Startup environment Unlimited paid time off

Regions: Remote/Anywhere North America
Country: United States

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