Datadog

Staff Software Engineer - ML Observability

Datadog
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1 day ago
Boston, MA, USA or New York, NY, USAStaff+
H1B Sponsor

Base Salary

$234k - $300k/yr

Responsibilities

  • Drive the design and implementation of LLM observability features.
  • Prototype and scale product features for monitoring and improving generative AI systems.
  • Develop tools for tracing, evaluating, and debugging LLMs.
  • Collaborate cross-functionally with engineering, product, UX, and applied science teams.
  • Influence architecture decisions and mentor engineers building resilient, high-performance systems.
  • Use customer pain points and industry developments to guide product and engineering priorities.

Requirements

  • Bachelor’s, master’s, or PhD in computer science, engineering, or a related scientific field, or equivalent experience.
  • Deep understanding of distributed systems and scalable backend architectures.
  • Hands-on experience building and shipping LLM-powered or generative AI applications.
  • Understanding of model internals, inference pipelines, evaluation techniques, and prompt engineering.
  • Experience with observability tools or platforms.
  • Ability to work in ambiguous, rapidly changing environments with a product-oriented mindset.
  • Clear communication, rigorous thinking, and commitment to clean, maintainable code.

Benefits

  • Hybrid workplace designed to support collaboration and work-life harmony.
  • Competitive global benefits that vary by country and employment arrangement.
  • Continuous professional development and learning opportunities.
  • Healthcare, dental, parental planning, mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.
  • Competitive salary and equity package, with variable compensation potentially included.

Tech Stack

Datadog
Datadog

About Datadog

1,001-5,000 employees

Datadog is the essential monitoring platform for cloud applications. We bring together data from servers, containers, databases, and third-party services to make your stack entirely observable. These capabilities help DevOps teams avoid downtime, resolve performance issues, and ensure customers are getting the best user experience.

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