
Engineering Manager, Site Reliability Engineering at Baseten (London, United Kingdom)
Baseten· London, United Kingdom· £185k–£276k·
Role details
Baseten at a glance
AI inference platform for deploying, optimizing, and running machine learning models in production at scale.
Baseten runs trained AI models in production for other companies, handling the GPUs, autoscaling, runtime, and performance tuning so engineering teams get a fast, reliable API without operating the infrastructure themselves. It supports open source, custom, and fine tuned models across managed cloud, hybrid, and self hosted deployments.
$2B+ raised · latest: Series F · $1.5B · June 2026 (valuations of $13B and $11B across two tranches) · backed by Altimeter Capital, Conviction, Spark Capital, Sands Capital
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, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.
RESPONSIBILITIES
- Recruit, hire, and grow Baseten’s first SRE team in London, with ongoing coaching, feedback, and career development through regular 1:1s.
- Set clear performance expectations, hold a high bar, and foster a culture of ownership, accountability, and continuous improvement.
- Own the reliability of Baseten’s multi-cloud Kubernetes infrastructure during your team’s hours, including incident response, post-mortems, and remediation tracking.
- Partner with SRE leadership in the US to design follow-the-sun on-call rotations, escalation paths, and handoff processes.
- Serve as the escalation point for major incidents, drive resolution with urgency, and make sure the team learns from every incident.
- Drive technical decisions through design reviews, code reviews, and architectural discussions. Turn the reliability roadmap into clear team priorities and milestones, and hold the team accountable for delivering them.
- Lead the team in defining and instrumenting SLOs and SLIs, and in building observability infrastructure (metrics, logging, dashboards, and alerting) as code.
- Turn recurring failure patterns and tribal knowledge into runbooks, automated mitigations, and self-healing systems.
- Partner with engineering, forward deployed, capacity, and product teams to raise the operational floor across the company, and represent your team’s progress, capacity, and tradeoffs clearly to leadership.
- Ensure the fleet is healthy and operational across all clusters. Interact with vendors and internal teams to remediate node failures and reliability concerns.
- Exercise and encourage good judgment on tooling and architectural tradeoffs, with a bias against unnecessary complexity.
REQUIREMENTS
- 4+ years of experience directly managing engineers in an SRE, cloud infrastructure, or platform engineering context.
- Extensive hands-on experience with Kubernetes, with the ability to engage credibly in architectural discussions and code reviews (multi-cloud experience across EKS, GKE, or similar is a strong plus).
- Strong background building and maintaining scalable production infrastructure.
- Strong foundation in observability tooling: metrics (VictoriaMetrics, Prometheus), logging (Loki, ELK), dashboards (Grafana), and alerting pipelines.
- Experience with infrastructure-as-code (Terraform, Helm) and GitOps workflows (Flux CD, ArgoCD).
- Experience leading incident response, running post-mortems, and building on-call rotations and runbooks.
- Track record of recruiting and growing engineering talent.
- Strong written and verbal communication skills, with the ability to collaborate across time zones and influence without direct authority.
- Openness to learning about ML infrastructure. Prior machine learning experience is not required.
- Ability to work onsite in our London office 3 days a week.
NICE TO HAVE
- Experience building a new team or establishing an engineering presence in a new region.
- Observability-as-code experience.
- Background in multi-cloud and hybrid environments.
- Familiarity with incident management platforms (incident.io or similar).
- Background in GPU infrastructure, or in diagnosing runtime issues around latency, memory behaviour, GPU utilisation, and concurrency.
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).
Why work at Baseten
- 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.