---
title: 'Software Engineer - Inference Platform at Baseten'
canonical: 'https://feeny.ai/job/software-engineer-inference-platform-baseten-san-francisco-c8ft1e43rhsm'
type: 'job'
last_seen: '2026-10-18'
---

# Software Engineer - Inference Platform at Baseten

- **Company:** [Baseten](https://feeny.ai/companies/baseten)
- **Location:** San Francisco, CA
- **Compensation:** $180k–$360k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-10-05
- **Last confirmed live:** 2026-10-18
- **Apply:** https://jobs.ashbyhq.com/baseten/14c4a663-0b1f-4c11-93ff-1359741ee456

## Job description

## ABOUT BASETEN

Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. 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. We're growing quickly and recently raised our [$1.5B Series F](https://www.baseten.co/blog/announcing-our-series-f/), led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.

## THE ROLE

We're looking for distributed systems engineers and product-minded generalists to build the distributed runtime that powers large-scale LLM inference on Baseten. Our inference platform empowers customers to deploy and operate cutting-edge models with industry-leading performance, scalability, and reliability. It also powers Model APIs, our hosted endpoints for the latest open-source models. You'll work across the stack, from the developer experience customers use to deploy models, through the libraries behind features like tool calling and reasoning, down to the systems that orchestrate deployments on Kubernetes and route traffic efficiently. Your job is to make sure every model on our platform is fast, reliable, and cost-efficient. You'll join a small, high-impact team at the intersection of distributed systems, model performance, infrastructure, and product, helping define how developers use AI models at scale. This role is ideal for engineers who enjoy owning systems in production, solving hard integration problems, and making complex infrastructure simple and reliable for users.

## EXAMPLE INITIATIVES

You'll get to work on these types of projects on our Inference Platform:

- [The Baseten Inference Stack at NVIDIA Dynamo Day](https://www.baseten.co/blog/nvidia-dynamo-day-baseten-inference-stack/)
- [2x faster inference with KV cache-aware routing](https://www.baseten.co/blog/how-baseten-achieved-2x-faster-inference-with-nvidia-dynamo/)
- https://www.baseten.co/blog/how-baseten-multi-cloud-capacity-management-mcm-powers-cloud-self-hosted-and-hybr/#comparing-deployment-options-cloud-vs-self-hosted-vs-hybrid

## RESPONSIBILITIES

- Build the infrastructure and orchestration systems that deploy and run large-scale distributed LLM inference, including routing, autoscaling, scheduling, and runtime management.
- Design, build, and operate Model APIs, with a focus on advanced inference capabilities: structured outputs (JSON mode, grammar-constrained generation), tool/function calling, and multimodal serving.
- Implement platform fundamentals such as API versioning, validation, usage metering, quotas, and authentication.
- Instrument deep observability (metrics, traces, logs) and build repeatable benchmarks for speed, reliability, and quality. Help set best practices for testing, release automation, and operational excellence.
- Debug and harden complex production systems spanning Kubernetes, distributed runtimes, networking, and GPU workloads to improve reliability and scalability.
- Partner with Inference Performance engineers and other teams to make new optimizations broadly available to customers and easy to configure.
- Own projects end to end, from architecture through deployment, monitoring, and iteration on customer feedback. Along the way, make thoughtful tradeoffs between performance, reliability, operational simplicity, and developer experience.

## REQUIREMENTS

- Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, or a related field, or equivalent practical experience.
- 3+ years building and operating distributed systems, backend infrastructure, or large-scale APIs where reliability, latency, and scale are first-class concerns.
- A proven track record of owning low-latency, reliable backend services, including rate limiting, auth, quotas, metering, and migrations.
- Infrastructure instincts with a feel for performance: profiling, tracing, capacity planning, and SLO management.
- Comfort debugging performance and reliability issues across multiple layers of the stack, from application behavior down to runtime and infrastructure internals.
- A strong sense of developer experience. You think about how systems are used, not just how they work.
- Eagerness to learn new languages, frameworks, and systems, and a real interest in inference engineering. Prior ML or LLM experience isn't required, though experience with model serving or inference systems is a plus.
- Excellent written communication and collaboration skills, including writing clear design docs and working across functions.

## NICE TO HAVE

- Experience with or contributions to LLM inference engines and frameworks such as vLLM, SGLang, TensorRT-LLM, TGI, or Dynamo.
- Deep Kubernetes experience, including operators and custom resources, plus familiarity with service meshes or API gateways.
- Experience with distributed scheduling, autoscaling, or service orchestration.
- Experience operating GPU workloads in production.
- A background in developer-facing infrastructure or APIs, or contributions to open-source infrastructure or ML systems.
- Familiarity with observability tooling, CI/CD systems, or release automation.

## BENEFITS

- Competitive compensation, including meaningful equity
- (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents
- Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
- Paid parental leave
- Fertility and family-building stipend through Carrot
- (U.S. only) Company-facilitated 401(k)
- 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. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

## About Baseten

## Company Overview
- **One-liner**: Baseten is an AI infrastructure platform that provides high-performance inference infrastructure for deploying, optimizing, and managing AI models in production.
- **Entity Type**: Private (Series F)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2019
- **Founders**: Tuhin Srivastava (CEO), Amir Haghighat (CTO), Phil Howes (Co-Founder & Chief Scientist)

## Core Business
- **Primary industry/industries**: AI Infrastructure / Cloud Computing / MLOps
- **Target customers**: B2B, targeting AI-native companies, enterprises, and developers building and deploying large-scale AI applications. Notable customers include Abridge, Cursor, Lovable, Notion, and OpenEvidence.
- **Mission or purpose statement**: Provide the tooling, expertise, and hardware needed for teams to bring performant AI products to market as quickly and reliably as possible. The company's core belief is that "inference is everything" and that the future of AI will consist of millions of specialized models embedded into every product and workflow.

## Products & Services
- **Baseten Cloud**: A fully-managed, global deployment platform for AI models. Provides out-of-the-box performance optimizations, 99.99% uptime, and massive horizontal scale. Supports single-tenant and self-hosted (hybrid) deployments.
- **Baseten Inference Stack**: The proprietary, underlying technology that powers the platform. Includes custom model runtimes (LLMs, embeddings, voice AI, image generation), advanced caching, custom kernels, and cutting-edge performance research. Claims 2x higher throughput and 10% lower latency for embeddings (BEI).
- **Baseten Chains**: Enables granular hardware and autoscaling for compound AI systems, reportedly powering 6x better GPU usage and cutting latency in half.
- **Frontier Gateway (Pre-optimized Model APIs)**: Allows users to instantly test and deploy pre-optimized versions of the latest open-source, custom, and fine-tuned models (e.g., Qwen, DeepSeek, GLM, gpt-oss).
- **Forward Deployed Engineering (FDE)**: A service offering where Baseten engineers work side-by-side with key customers to build, optimize, and scale their models from prototype to production.
- **Training on Baseten**: Allows users to train models and deploy them in one click on the inference-optimized infrastructure.
- **Monetization API**: An inference API that allows model developers to monetize their models.

## Market Standing
- **Valuation/Market Cap**: Not privately disclosed, but the company has raised a total of **$585M** in funding.
- **Key Metric**: Annual revenue of **$7.0M** (as per LinkedIn). Total funding of **$585M**.
- **Notable Investors/Partners**: IVP, Spark Capital, Bond, CapitalG, South Park Commons, Greylock.
- **Growth Signals**:
    - Announced a **Series F** funding round (details not fully public in search results).
    - **Massive headcount growth**: 224.4% year-over-year, now employing 201 people.
    - **LinkedIn follower growth**: 199.9% year-over-year.
    - **Active job postings**: 112 open roles.
    - Acquired the company **Parsed**.
    - Backed by high-profile institutional investors including CapitalG (Alphabet's growth fund) and IVP.

## Competitive Advantages
- **High-Performance Inference Stack**: A proprietary, deeply optimized stack focusing on ultra-low latency and high throughput for the most demanding Gen AI workloads (voice AI, real-time streaming, complex compound AI systems).
- **Customer Obsession & Forward Deployed Engineering**: A hands-on, consulting-style approach with their FDE team, which builds deep, sticky relationships with high-value customers like Abridge and Notion.
- **Global & Hybrid Cloud Flexibility**: Offers both fully-managed cloud and self-hosted deployments within customer VPCs, providing scalability and security for enterprises with strict data governance requirements.
- **Founding Team's Deep Technical Credibility**: Built by former researchers and engineers who experienced the "deployment hell" of AI systems firsthand, giving them deep empathy and expertise in the problem they are solving.

## Strategic Focus
- **Dominating the "Inference-as-a-Service" Market**: The company's core thesis is that inference will become the largest market ever created, and they are building the infrastructure to power it.
- **Scaling for High-Volume, Mission-Critical Workloads**: Focus on reliability, performance, and cost-efficiency for customers who cannot afford downtime or latency (e.g., AI phone calls, real-time translation).
- **Deepening the Technical Stack**: Continuously investing in performance research (custom kernels, new decoding techniques) and expanding capabilities into new areas like voice AI and audio streaming.
- **Aggressive Hiring**: With 112 open positions and massive YoY growth, scaling the engineering, sales, and operations teams is a clear priority.

## Why Work Here
- **Hard Technical Problems**: Engineers work on the most challenging problems in modern infrastructure—model serving, low-level GPU optimization, networking, distributed systems, and observability. This is a high-agency, high-impact engineering environment.
- **High Growth Trajectory**: The company is experiencing explosive growth (224% headcount increase, active hiring). This offers significant career acceleration and ownership opportunities.
- **Strong Engineering Culture**: Founded by engineers, for engineers. The culture emphasizes "first-principles thinking across the entire stack" and a "customer-obsessed" mindset. The employer rating on compensation, culture, and work-life balance is rated highly (5.0).
- **Top-Tier Team & Investors**: The team has strong talent density with hires from Meta, Stripe, Google, NVIDIA, and Databricks. Being backed by top-tier VCs provides stability and a clear long-term vision.
- **Hybrid/In-Office**: Based in San Francisco with a strong in-person or hybrid culture common for fast-moving infrastructure startups.

## Sources
1. [Company Website](https://www.baseten.co/)
2. [Careers Page](https://www.baseten.co/resources/careers/)
3. [About Us (Team)](https://www.baseten.co/about-us/)
4. [LinkedIn Company Profile](https://www.linkedin.com/company/baseten)
5. [Ashby Careers Portal](https://jobs.ashbyhq.com/baseten)

## Other roles at Baseten

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- [Partner Enablement Lead](https://feeny.ai/job/partner-enablement-lead-baseten-san-francisco-hnn1ex9bg330) — San Francisco, CA
- [Engineering Manager Runtime - Storage](https://feeny.ai/job/engineering-manager-runtime-storage-baseten-san-francisco-tj58p3wmtdwz) — San Francisco, CA
- [Sales Manager - Enterprise (New York)](https://feeny.ai/job/sales-manager-enterprise-new-york-baseten-new-york-5tyvjykwwgvp) — New York, NY
- [GRC Manager](https://feeny.ai/job/grc-manager-baseten-san-francisco-h4rsmvjx5r79) — San Francisco, CA
- [Post-Training Applied Researcher](https://feeny.ai/job/post-training-applied-researcher-baseten-san-francisco-rkqr55d1q922) — San Francisco, CA
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