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Generative AI Data Scientist & ML Engineer
Royal Bank of Canada
Toronto, ON
Full-time
Collaborative Research: Collaborate with other data scientists, machine learning engineers, and domain experts to identify new opportunities for applying LLMs and AI agents, and contribute…
Software Engineer - GPU Networking & Distributed Systems
Baseten
Montreal, Quebec
$165,000 to $330,000 USD / year
Full-time
…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…
Artificial Intelligence Engineer
Precision AI
Calgary, Alberta
Full-time
The Artificial Intelligence Engineer at Precision AI will contribute to the design, development, and deployment of AI-driven solutions. This role focuses on building, training, and…
Intern Engineer – RL Post-Training for LLMs
Huawei Technologies Canada Co., Ltd.
Vancouver, BC
Internship
Collaborate with researchers and engineers on cutting-edge LLM projects
ML Engineer
Tigera
Vancouver, BC
…make decisions, call tools, hold credentials, and reach across systems in ways traditional models weren't designed for. The companies running thousands of these agents in production have…
Senior Data Scientist | Scientifique de données senior
Jesta I.S.
Westmount, Quebec · Montreal, Quebec
Full-time
…enterprise applications that combine predictive analytics, machine learning, generative AI, agentic AI, and computer vision directly within business workflows. Our AI Centre of Excellence…
Senior AI Software Developer (Canada Remote)
Autodesk
Toronto, ON · AMER - Canada - Ontario - Offsite/Home
Full-time
Autodesk is leading the transformation of how users interact with design and engineering software by embedding AI deeply into our products. We are building cloud-native, AI-powered…
Specialist, AI Engineering
Definity Insurance Company
Toronto, ON
Full-time
AI Application Development: An AI Engineer is focused on the practical application of artificial intelligence and machine learning to create intelligent systems and solve real-world…
Principle Developer
Ericsson
Ottawa, ON
Full-time
Minimum 12 years as a systems engineer or research engineer
Principal Developer
Ericsson
Ottawa, Ontario
Full-time
Minimum 12 years as a systems engineer or research engineer
Lead Software Engineer - Enterprise Applications
Citi
Mississauga, ON
Full-time
2+ years focused on AI software development, LLM‑based solutions, agentic systems, and/or machine learning.
AI Developer
GenAIz
Montreal, Quebec
Full-time
Certification in machine learning or data science (e.g., Certified Data Scientist, Certified Machine Learning Engineer)
Applied Scientist, Pro Growth
Javelin Venture Partners
ON · Ontario, Canada
Full-time
Master’s degree in a quantitative field (Computer Science, Machine Learning, Statistics, Operations Research, Economics, or related), or equivalent industry experience.
Applied Scientist, Pro Growth
Thumbtack
Remote, Canada
Full-time · Remote
Master’s degree in a quantitative field (Computer Science, Machine Learning, Statistics, Operations Research, Economics, or related), or equivalent industry experience.
AI Solutions Architect
HireHawk
Remote, Canada
Full-time · Remote
3+ years of experience in Software Engineering, AI Engineering, Machine Learning Engineering, or a related technical field.
Ingénieur(e) principal(e) en réseaux de puissance / Lead Power System Engineer
Eaton Corporation
Brossard, QC
Full-time
Eaton's Electrical Engineering Services and Systems division is currently seeking a Lead Power System Engineer. This role is based in our Eaton Americas Innovation Center in Brossard,…
Principal Cloud Security Engineer
BMO
Toronto, ON · BMOPLACE
Full-time
We are seeking an enthusiastic and passionate professional for a Senior Cloud, AI & Data Security Engineer role who wants to design and implement security solutions for systems and services…
Winter 2027: WiSE AI Developer Co-op (4 months)
CGI
Toronto, ON
Full-time
Build solutions leveraging Large Language Models (LLMs), including prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, tool/function calling, and agentic AI patterns.
Lead AI/ML Engineer
RBC
Toronto, ON
Full-time
5+ years of experience in software development with 3+ years focused on machine learning and AI solutions
Senior AI/ML Engineer
RBC
Toronto, ON
Full-time
Proficiency in programming languages such as Python, with experience in machine learning libraries (e.g., TensorFlow, PyTorch).
Senior AI/ML Engineer
Royal Bank of Canada
Toronto, ON
Full-time
Proficiency in programming languages such as Python, with experience in machine learning libraries (e.g., TensorFlow, PyTorch).
Lead AI/ML Engineer
Royal Bank of Canada
Toronto, ON
Full-time
5+ years of experience in software development with 3+ years focused on machine learning and AI solutions
RAG Engineer
MCI Careers
Canada
Other
Minimum 3 years of experience in software engineering, AI engineering, machine learning, or information retrieval.
AI/ML Engineer
TC Transcontinental
Mississauga, ON
Full-time
Design and build machine learning and generative AI components that integrate with our data platforms and infrastructure, built for automation, reliability, and operational efficiency.
Sr. Computer Vision Engineer
OpenSpace
Canada
We're looking for an experienced Sr. Computer Vision Engineer to own core algorithms for mapping, localization, image analysis, and 3D reconstruction on real-world construction site data.…

Baseten

Software Engineer - GPU Networking & Distributed Systems

Montreal, QC, Canada

Pay: $165,000 to $330,000 USD / year
Job type: Full-time
Posting language: English
Posted: Jul 10, 2026

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Original 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 to ship AI products.

At Baseten, we are building the global operating system for distributed, heterogeneous AI hardware. We believe that as LLM and multi-modal workloads scale, the network is the computer. We are looking for foundational engineers to lead our GPU Networking efforts, making RDMA a first-class building block in our infrastructure and unlocking the next generation of distributed inference optimizations.

THE OPPORTUNITY

Networking and compute are no longer separate disciplines; they are converging. The massive throughput of H100, B200, and NVL72 architectures enables and demands a new approach where communication is co-optimized alongside computation. We are entering an era where the network is an active accelerator, leveraging smart hardware offloads and direct interconnects to ensure that data movement operates at wire-speed.

In this role, you will go beyond network configuration to architect the software fabric that unifies thousands of GPUs into a cohesive operating system. While you will leverage the best of the open-source ecosystem, you won't be limited by it. Where off-the-shelf solutions stop, you will build from scratch, engineering the primitives required to co-optimize communication and compute for Disaggregated Serving, Wide Expert Parallelism (WideEP), and lightening cold starts.

What You'll Do

Make RDMA First-Class: You will work on integrating RDMA/RoCE/InfiniBand capabilities directly into our inference stack, helping us move beyond TCP/IP to unlock order-of-magnitude improvements in bandwidth and latency.
Optimize Distributed Inference: You will implement and tune the networking layers necessary for efficient Disaggregated KV Cache Offload and WideEP, ensuring seamless communication across NVLink and InfiniBand for our MoE models.
Enable Serverless-Grade Startup Speeds for LLMs: You will work deeply with checkpointing and storage mechanisms to enable sub-10-second startup for trillion-parameter models.
Deep-Dive into Hardware: You will characterize and validate networking performance on bleeding-edge clusters (H100/H200, B200/B300, GB200/300 NVL72), writing the acceptance tests that ensure our hardware delivers peak achievable throughput and minimal latency.
Build Observability: You will design the tools that let us visualize packet flow, congestion, and effective bandwidth across the GPU interconnects, helping us diagnose complex distributed system behaviors.
Optimize Kernels: You will work with communication libraries (NCCL, NVSHMEM) and potentially write custom communication kernels to overlap compute and data transfer.

Who You Are

You have deep experience with high-performance networking protocols (InfiniBand, RoCE v2) and understand the physics of data movement.
You are fluent in C++ or Python, with the ability to bridge the gap between high-level logic and hardware. You have a deep understanding of the memory hierarchy in modern NVIDIA architectures (H100/Blackwell) and know how to optimize for it.
You like going deep. You aren't afraid to dive into TensorRT-LLM source code, write custom C++ / Python bindings, or debug NVLink topology issues.
You know when to use an off-the-shelf solution and when we need to build a custom solution because the upstream tools (like standard Kubernetes networking) are too slow for our needs.

HIGHLY PREFERRED:

Deep knowledge of NCCL, NVSHMEM, and UCX.
Experience with GPUDirect Storage (GDS) or high-performance filesystems like Weka or 3FS.
Familiarity with TensorRT-LLM, vLLM, or Sglang.
Experience running low-level benchmarks to "qualify" new hardware clusters.

Why join the Model Performance team?

Bleeding Edge Hardware: We are preparing to bring Blackwell (B200/B300) and then Rubin architectures online. You will be one of the first engineers in the industry optimizing networking for NVL72/GB300 racks.
We go deep: We operate at every depth. Whether it’s tuning hardware interconnects, writing custom communication kernels, or designing distributed inference strategies, we work across the entire stack to deliver performance that goes far and beyond.
High Impact: The networking optimizations you build will directly enable features that no one else in the industry has fully mastered yet, like seamless multi-node WideEP and instant model hydration.

Benefits

Competitive compensation, including meaningful equity.
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
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).

Compensation Range: $165K - $330K

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More about this job

Responsibilities

You will architect the software fabric that unifies thousands of GPUs into a cohesive operating system, integrating RDMA capabilities into the inference stack. Additionally, you will optimize distributed inference and enable serverless-grade startup speeds for large language models.

Requirements

Candidates should have deep experience with high-performance networking protocols and be fluent in C++ or Python. A strong understanding of modern NVIDIA architectures and the ability to optimize for them is also essential.

Skills

High-Performance Networking Protocols
C++
Python
Memory Hierarchy
TensorRT-LLM
NCCL
NVSHMEM
UCX
GPUDirect Storage
High-Performance Filesystems
Distributed Inference
Networking Layers
Data Movement
Custom Communication Kernels
Observability Tools
Acceptance Tests

Benefits

Competitive Compensation
Health Insurance
Flexible PTO
Paid Parental Leave
Fertility and Family-Building Stipend
401k

Visa sponsorship

Not detected in the job text

Keywords

Software Engineer
GPU Networking
Distributed Systems
AI
Inference
RDMA
RoCE
InfiniBand
TCP/IP
Disaggregated Serving
Wide Expert Parallelism
Checkpointing
Storage Mechanisms
Networking Performance
Bleeding-Edge Clusters
Packet Flow
Congestion
Effective Bandwidth
Communication Libraries
Custom Communication Kernels
NVIDIA
H100
B200
NVL72
TensorRT
Model Performance
Blackwell
Rubin Architectures
High Impact

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