Software Engineer, ML Infrastructure
Serve Robotics119,000 - 160,000 USD/year
- Full Time
- Junior (1 to 2 years)
$150,000 – $200,000Compensation
Junior (1 to 2 years)Experience Level
Full TimeJob Type
UnknownVisa
AI & Machine Learning, Enterprise Software, Data & AnalyticsIndustries
Requirements
Candidates must have a Bachelor's degree or higher in Computer Science or a related field. They should possess 1-3 years of experience in software engineering or infrastructure, with proficient coding abilities in one or more popular programming or scripting languages, preferably Go. A working knowledge of Kubernetes and containerization is required, along with a basic understanding of machine learning concepts and model serving. Familiarity with distributed systems concepts and experience with basic monitoring and logging tools are also necessary. Candidates should have an interest in ML/AI infrastructure and a willingness to learn, as well as strong collaboration and communication skills.
Responsibilities
The Infrastructure Software Engineer will develop infrastructure components for the ML inference platform using Python and Go. They will implement and maintain Kubernetes deployments for model serving and contribute to the inference orchestration layer for model deployments. The role involves building and enhancing monitoring systems for model performance metrics, implementing efficient resource management solutions for ML workloads, and supporting infrastructure automation to improve ML deployment workflows. The engineer will work closely with team members to implement technical solutions, balance performance optimization with system reliability, participate in technical discussions around infrastructure improvements, and learn and apply infrastructure best practices.
Skills
Python
Go
Kubernetes
Infrastructure
Monitoring
Resource Management
Automation
Software Engineering
Baseten
Platform for deploying and managing ML models
About Baseten
Baseten provides a platform for deploying and managing machine learning (ML) models, aimed at simplifying the process for businesses. Users can select from a library of open-source foundation models and deploy them with just two clicks, making it easier to implement ML solutions. The platform features autoscaling, which adjusts resources based on demand, and comprehensive monitoring tools for tracking performance and troubleshooting. A key differentiator is Baseten's open-source model packaging framework, Truss, which allows users to package and deploy custom models easily. The company operates on a usage-based pricing model, where clients pay only for the time their models are actively deployed, helping them manage costs effectively.
Key Metrics
San Francisco, CaliforniaHeadquarters
2019Year Founded
$58.4MTotal Funding
SERIES_BCompany Stage
AI & Machine LearningIndustries
51-200Employees