Software Engineer - Infrastructure

Reposted 17 Days Ago
3 Locations
In-Office or Remote
150K-230K Annually
Junior
Software
The Role
Develop and maintain components for machine learning inference platform. Focus on Kubernetes deployments, resource management, and performance monitoring.
Summary Generated by Built In

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 an Infrastructure Software Engineer at Baseten, you'll build and maintain components of our ML inference platform that powers production AI applications. You'll contribute to the core infrastructure, enabling developers to deploy, scale, and monitor ML models with high performance.

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

  • Develop infrastructure components for our ML inference platform using Python and Go

  • Implement and maintain Kubernetes deployments for model serving

  • Contribute to our inference orchestration layer for model deployments

  • Build and enhance monitoring systems for model performance metrics

  • Implement efficient resource management solutions for ML workloads

  • Support infrastructure automation to improve ML deployment workflows

  • Work closely with team members to implement technical solutions

  • Help balance performance optimization with system reliability

  • Participate in technical discussions around infrastructure improvements

  • Learn and apply infrastructure best practices

REQUIREMENTS

  • Bachelor's degree or higher in Computer Science or related field

  • 1-3 years experience in software engineering or infrastructure

  • Proficient coding abilities in one or more popular programming or scripting languages; Go proficiency is a plus

  • Working knowledge of Kubernetes and containerization

  • Basic understanding of machine learning concepts and model serving

  • Familiarity with distributed systems concepts

  • Experience with basic monitoring and logging tools

  • Interest in ML/AI infrastructure and willingness to learn

  • Strong collaboration and communication skills

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.

Top Skills

Go
Kubernetes
Python
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The Company
59 Employees

What We Do

At Baseten we provide all the infrastructure you need to deploy and serve ML models performantly, scalably, and cost-efficiently.

Get started in minutes, and avoid getting tangled in complex deployment processes. You can deploy best-in-class open-source models and take advantage of optimized serving for your own models.

We also utilize horizontally scalable services that take you from prototype to production, with light-speed inference on infra that autoscales with your traffic.

Best in class doesn't mean breaking the bank. Run your models on the best infrastructure without running up costs by taking advantage of our scaled-to-zero feature

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