Forward Deployed SRE, Baseten
$150-225k
+ Equity
ML application builder for data scientists
Open for applications
ML application builder for data scientists
21-100 employees
Open for applications
$150-225k
+ Equity
21-100 employees
Company mission
To make machine learning accessible to every organisation.
Role
Who you are
- Deep Kubernetes troubleshooting expertise, including advanced resource debugging, pod/runtime analysis, and log-based diagnostics using observability tooling such as Grafana, Loki, and Prometheus
- Strong infrastructure debugging ability across container orchestration, networking, and service dependencies, with hands-on experience supporting production-grade clusters
- Experience managing high-severity incidents with major customers, including SLAs, post-incident reviews, and clear communication throughout escalations
- Proven project management and organizational skills with an ownership mindset, able to manage multiple complex, multi-stakeholder initiatives in parallel — including issue resolution, root-cause analysis, and feature delivery
- Ability to translate recurring technical pain points into roadmap-level insights, documentation improvements, or product enhancements
- Strong communication skills and executive presence during high-visibility situations, ensuring technical clarity and customer confidence
- 3+ years of experience in a fast-paced, high-growth, or customer-facing engineering environment
Desirable
- Familiarity with running high-performance AI models and workloads, including troubleshooting ML pipelines from preprocessing through inference and serving
- Experience implementing or managing ticketing and incident-response systems such as Zendesk or Pylon
- Familiarity with Helm, Flux, CI/CD tooling, or scripting automations to improve deployment, release, or operational workflows
What the job involves
- You will serve as the primary post-sales technical owner for our most strategic customers, ensuring smooth deployment, performance, and reliability of ML workloads in production
- You’ll own the technical success and long-term outcome of our strategic and enterprise accounts by managing and resolving escalations, maintaining and improving our runbooks, and proactively surface patterns that drive product improvements
- This role blends hands-on debugging, infrastructure expertise, AI model performance monitoring, and executive-level customer-facing ownership
- You’re of course not alone in this endeavor — partnering closely with product, engineering, and forward-deployed teams to remove technical friction, drive adoption, and ensure long-term success for high-value accounts
- Diagnose and resolve runtime issues related to latency, memory behavior, GPU utilization, concurrency, and model lifecycle management
- Debug infrastructure issues across Kubernetes (pods, controllers), networking, observability, and alerting systems
- Lead incident response during outages or escalations, managing coordination between Product, FDE, Sales, and Engineering
- Serve as the technical owner for top enterprise accounts with strict SLAs and high responsiveness expectations
- Identify common failure modes and translate user feedback into roadmap signals, product improvements, our internal runbooks, knowledge bases, and diagnostic best practices
- Own project coordination end-to-end: scoping, execution, communication, and stakeholder alignment across technical and non-technical teams ranging from feature requests, new deployments, and operational debugging issues
Our take
As with its mathematical namesake, Baseten focuses on simplifying the complex. The San Francisco startup focuses on simplifying the integration of artificial intelligence into businesses. The tools that Baseten built demolish the need for businesses to hire specialised engineers, utilising the huge strides in artificial intelligence that we’ve seen in the last few years without adding workload to businesses.
With serious funding behind it, Baseten has grown its team by three times year-over-year over the last five years, especially across engineering and marketing. Having hired talent from companies such as GitHub, Google, Uber, Amazon, and Palantir, part of Baseten's focus is on helping companies implement the tools that they have at their disposal, a long-overlooked aspect of machine learning that many businesses have been eager to champion, but uncertain on how to actually use.
Simplifying the complex world of artificial intelligence for business is no mean feat but the three founders, who met whilst working as engineers at Gumroad, have a lot of experience in how to navigate this gap in the market.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 6 rounds)
Jan 2026
$300m
LATE VC
Sep 2025
$150m
SERIES D
Total funding: $585m
Company benefits
- Remote-first work environment. The Baseten team is welcome to work from wherever they want; fully remote, in our San Francisco office, or a mix of both. Today, our team (including our founding team) is spread across the United States, Canada, and Armenia. We provide a $1,000 stipend for you to make your home-office comfortable and productive
- Regular in-person team summits. We get together as a team three times a year to plan, workshop, and most importantly, get to know each other better
- Unlimited PTO. We ask that everyone take at least 4 weeks of vacation. And we have a company-wide break between Christmas and New Year's Day
- Full healthcare coverage. Medical, dental and vision insurance for you and your family
- Paid parental leave. 16-weeks fully paid parental leave (adoptive and non-birth parents included) and flexibility with schedules while returning to work
- Company-sponsored 401(k) for you to contribute to
- Learning and development budget. We encourage you to take classes, attend conferences, and invest in your craft and we’ll cover expenses to make it happen
Company HQ
Union Square, San Francisco, CA
Leadership
Tuhin Srivastava
(Co-Founder)Previously Co-Founder at Shape, Machine Learning at Gumroad and Skulpt.
Amir Haghighat
(Co-Founder)Previously Head of Engineering at Gumroad, Software Engineer at Yelp and Engineering Manager at Clover Health.
Phillip Howes
(Co-Founder)Previously Co-Founder at Shape, Machine Learning Engineer at Gumroad and Research Assistant at the University of Sydney.
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