Sr. Software Engineer, ML Platform

Cursor
Palo Alto, CA
On-site

Who this role is best for

Distributed-systems engineers with ML platform experience will find this high-ownership role in a collaborative, research-facing environment.

Best fit for

  • Candidates with 5+ years in distributed systems and a background in ML infrastructure will thrive here.
    — “5+ years of industry experience working with production distributed systems”
  • Individuals who excel in high-ownership environments and enjoy iterative platform development are ideal.
    — “Ship iteratively in a flat, high-ownership environment”
  • Professionals with experience in GPU scheduling and observability tooling for ML systems are well-suited.
    — “ML DevX and Systems: GPU / cluster scheduling, job queues, node health, research compute developer experience”

Things to consider

  • In-office presence is required in select locations like San Francisco, Palo Alto, and New York.
    — “We're in-person with cozy offices in North Beach, San Francisco, Palo Alto, and Manhattan, New York”
  • The role requires passing a technical screening process with 2-3 short technical interviews.
    — “we'll reach out to schedule 2-3 short technicals”

How to stand out

  • Highlight experience in building durable infrastructure for ML research teams.
    — “Partner closely with research to turn recurring pain into durable infrastructure”
  • Emphasize ownership of production systems at scale, particularly in data pipelines or scheduling.
    — “Experience owning production distributed systems at meaningful scale”
  • Showcase telemetry and observability work, especially with OpenTelemetry and agent-friendly UX.
    — “Telemetry: event ingestion, product analytics pipelines, OpenTelemetry / tracing, reliable data APIs”
  • Demonstrate expertise in ML dataset and training-data infrastructure using frameworks like Spark or Ray.
    — “Product Data Platform: data frameworks, Spark / Flink / Ray, ML dataset and training-data infrastructure”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • design, build, and operate core platform systems
  • partner with research to turn recurring pain into durable infrastructure
  • own reliability, performance, and developer experience for systems
Typical background
5+ years of industry experience working with production distributed systemsbachelor's, master's, or phd in computer science, machine learning, or another quantitative discipline

Skills & requirements

Required

Distributed-systemsInfrastructure-engineeringProduction-distributed-systemsTelemetryProduct-data-platformObservabilityMl-devx-and-systems

Preferred

Grok-modelsColossus-supercomputersGrok-botGrok-buildGrok-imagineGrok-voiceX

Stack & domain

Distributed-systemsInfrastructureProduction Distributed SystemsTelemetryProduct Analytics PipelinesOpentelemetry / TracingReliable Data ApisProduct Data PlatformSpark / Flink / RayML Dataset And Training-data InfrastructureObservabilityExperiment / Run MonitoringDebug And Eval ToolingAgent-friendly Observability UXML Devx And SystemsGPU / Cluster SchedulingJob QueuesNode HealthResearch Compute Developer ExperienceLeadershipProblem-solvingOwnershipCommunicationCollaborationNegotiationCommercial Risk AllocationContract AdministrationSoftware EngineeringMachine LearningData ScienceCloud ComputingAIData AnalyticsDevOps

About the role

Original posting from Cursor via Ashby

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.

SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.

SR. SOFTWARE ENGINEER, ML PLATFORM

As a Software Engineer on ML Platform at SpaceXSI, you'll build the infrastructure that turns real product usage into better models, and keeps research moving fast on large GPU fleets. ML Platform is organized into four teams. Depending on your background, you may join any of them. We're looking for strong distributed-systems and infrastructure engineers who want to sit next to research and ship platform primitives that move the product.

RESPONSIBILITIES:

  • Design, build, and operate core platform systems used daily by ML researchers and product engineers
  • Partner closely with research to turn recurring pain into durable infrastructure
  • Own reliability, performance, and developer experience for the systems in your lane
  • Ship iteratively in a flat, high-ownership environment. Measure impact, then raise the bar

BASIC QUALIFICATIONS:

  • Bachelor's, Master's, or PhD in computer science, machine learning, or another quantitative discipline; OR equivalent work experience
  • 5+ years of industry experience working with production distributed systems (e.g., infrastructure, ingestion, data pipelines, or scheduling/orchestration, etc.)

PREFERRED SKILLS AND EXPERIENCE:

  • Experience owning production distributed systems at meaningful scale (ingestion, data pipelines, scheduling/orchestration, or similar)
  • Experience partnering and building platforms for ML researchers and product engineers
  • Thrive where ownership is high and the feedback loop is short
  • Telemetry: event ingestion, product analytics pipelines, OpenTelemetry / tracing, reliable data APIs
  • Product Data Platform: data frameworks, Spark / Flink / Ray, ML dataset and training-data infrastructure
  • Observability: experiment / run monitoring, debug and eval tooling, agent-friendly observability UX
  • ML DevX and Systems: GPU / cluster scheduling, job queues, node health, research compute developer experience

ADDITIONAL REQUIREMENTS:

  • We're in-person with cozy offices in North Beach, San Francisco, Palo Alto, and Manhattan, New York, complete with well-stocked libraries
  • If there appears to be a fit, we'll reach out to schedule 2-3 short technicals. After, we'll schedule an onsite in our office, where you'll work on a small project, discuss ideas, and meet the team

COMPENSATION AND BENEFITS:

The annual compensation range for this role is listed below.

Annual Salary:

$180,000 - $330,000 USD

Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, and experience.

Base salary is just one part of our total rewards package at SpaceXSI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

Source: Cursor careers (Ashby)

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