Baseten

HQ
San Francisco
Total Offices: 2
350 Total Employees
Year Founded: 2019

Baseten Benefits Overview

Compensation + Benefits

Offers company equity

Offers competitive compensation and rewards package

Provides relocation assistance

Offers dental insurance

Offers health insurance

Offers Health Savings Account (HSA)

Offers Flexible Spending Account (FSA)

Offers vision insurance

Offers generous parental leave

Provides an onsite Mother's Room

Provides fertility benefits

Company Culture

Provides free daily meals

Provides free snacks and drinks

Work-Life Balance + Wellbeing

Offers a flexible time off policy

Including company wide Winter Break — our offices are closed from Christmas Eve to New Year's Day

Recently posted jobs

4 Days AgoSaved
Remote or Hybrid
5 Locations
Software
Manage and mature Baseten’s security governance, risk, compliance, privacy, audit, certification, vendor assessment, and customer assurance programs. Translate regulatory and customer requirements into technical controls and product requirements, partnering with Engineering, Product, Security, Legal, and Operations. Coordinate SOC 2, ISO, HIPAA, FedRAMP, and related audits; manage risk assessments, evidence collection, remediation, security questionnaires, training, and continuous improvement in a fast-growing AI platform company.
6 Days AgoSaved
Hybrid
5 Locations
Software
Develop and productionize high-performance LLM inference techniques across runtimes, scheduling, serving, routing, and GPU kernels. Profile and optimize latency, throughput, memory usage, and cost; support new models and hardware; build benchmarking frameworks; and contribute to open-source inference engines such as vLLM, SGLang, and TensorRT-LLM. The role requires strong programming, GPU architecture, ML library, and LLM optimization knowledge.
6 Days AgoSaved
Hybrid
5 Locations
Software
Build and operate the distributed inference platform powering large-scale LLM deployments. Responsibilities include orchestration, routing, autoscaling, scheduling, Model APIs, authentication, quotas, metering, observability, benchmarking, and production reliability across Kubernetes, networking, distributed runtimes, and GPU workloads. The role owns projects end to end and partners with performance engineers to deliver efficient, scalable AI inference capabilities and strong developer experiences.