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Senior AI Research Engineer - GPU Systems & Kernels

DatadogParis, FranceFull-timeSalary not listed · Typical pay in FrancePosted Nov 9, 2026

Datadog has an opening for a Senior AI Research Engineer - GPU Systems & Kernels in Paris, France. The listing describes it as a full-time, senior position with hybrid working.

Written by Dev Global Jobs

DGJ summary of this job

Our own short read of this listing, built only from the facts it gives. The employer’s original text follows further down.

Datadog has an opening for a Senior AI Research Engineer - GPU Systems & Kernels in Paris, France. The listing describes it as a full-time, senior position with hybrid working.

The advert mentions Python, Rust, C++ and observability among the skills and tools for this role.

The employer does not state a salary in this listing; DGJ Insight below shows an official pay benchmark for the place where one exists.

Benefits mentioned in the advert: bonus.

Visa sponsorship is not mentioned. Applicants from outside France should check the official work permit route before applying.

Dev Global Jobs found this job on Greenhouse on Nov 9, 2026.

Employer
Datadog
Location
Paris, France
Work mode
hybrid
Job type
Full-time
Level (from the title)
senior
Pay
Not stated by the employer
Found
Nov 9, 2026 on Greenhouse
Employer text
755 words, about 3 min to read
Skills named in the advert
PythonRustC++observability
Before you apply
  • Apply only on the official page (careers.datadoghq.com). Dev Global Jobs is not the employer and never asks for a fee.
  • Mirror the skills the advert names (Python, Rust, C++ and observability) in your CV where you really have them; applicant tracking systems look for these words.
  • Read the employer’s full text below (about 3 min) before you apply.
  • Build or check your CV with the free DGJ CV Builder.
Only on Dev Global Jobs

DGJ Insight

Our own data about this role and place, from official statistics and our live job index.

Updated Nov 9, 2026
Pay benchmark
Average wage, France
EUR 44,304 average / year

Source: OECD Average annual wages, 2025

Cost of living · Paris
85.7 vs New York = 100

UN living-cost index for Paris (ICSC post adjustment 50.5), as of 1 Oct 2026.

Source: ICSC post adjustment classifications (icsc.un.org)

Work permit route
  • Talent Passport: Qualified employees, researchers, artists, investors; multi-year permit
  • Employee (salarié) visa: Employer work authorisation from the labour office
  • Temporary worker visa: Contracts under 12 months
Job description

About the role

Full text from the employer, as published on Greenhouse, arranged into sections. Nothing added or removed.

As a Research Engineer on the Frontier Foundations team, you will partner with Research Scientists to make large-scale model training and inference as fast and efficient as the hardware allows. You will work at the lowest level of our stack, writing and tuning GPU kernels and removing the memory and communication bottlenecks that limit large Mixture-of-Experts models on the latest GPUs.

Building on our track record of AI-powered solutions (e.g., Bits AI, Bits Evolve, and our time series foundation model Toto), Datadog AI Research (DAIR) tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security.

Frontier Foundations builds and maintains the high-performance infrastructure that lets us train and serve large language models at scale. It supports both of our research areas:

Trained Agents for Observability - Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost.

01What You'll Do

  • Write, tune, and debug GPU kernels (CUDA, Triton, or similar) for the operations that dominate LLM training and inference.
  • Optimize for the latest NVIDIA GPU generations, including memory hierarchy, tensor cores, and low-precision formats such as FP8 and FP4
  • Reduce communication cost in distributed workloads (all-to-all, all-reduce) and overlap communication with compute across NVLink and across nodes
  • Profile end-to-end training and rollout workloads to identify whether they are compute-, memory-, or communication-bound, and quantify the headroom
  • Build benchmarks, profiling tools, and regression tests that guide optimization decisions
  • Collaborate with Research Scientists to turn new model architectures into efficient implementations
  • Explore emerging techniques such as low-precision training and serving, speculative decoding, and fused or persistent kernels

02Who You Are

  • You have depth in at least one of: GPU kernel development and optimization (CUDA or similar), low-latency communication and collective operations (e.g., RDMA, NCCL), or large-scale training infrastructure
  • You can reason about hardware constraints (memory, bandwidth, interconnect topology) and explain where a bottleneck is and how you would confirm it
  • You are proficient in a systems language (e.g., C++, Rust, or CUDA C) and in Python
  • You have strong debugging and profiling skills, including tools such as Nsight
  • You can explain design and performance trade-offs clearly to both technical and non-technical audiences

03Bonus Points (any of the following)

  • You have experience with Mixture-of-Experts models, expert parallelism, or sparse model inference
  • You are familiar with GPU communication libraries such as NCCL or NVSHMEM, and with compute/communication overlap
  • You have experience with Triton, CUTLASS, or similar kernel frameworks
  • You are familiar with distributed training frameworks such as Megatron-LM, TorchTitan, or DeepSpeed
  • You have built GPU-intensive systems in graphics, rendering, simulation, or scientific computing
  • You have contributed to open-source ML or systems infrastructure projects

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you're passionate about technology and want to grow your skills, we encourage you to apply.

#LI-Hybrid


04About Datadog

Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.


05Equal Opportunity at Datadog

Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.

Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications.

06Privacy and AI Guidelines

Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.

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