Software Engineer, TT-Distributed

Tenstorrent • Toronto, ON

1d • $100,000 - $500,000 • Hybrid

About The Position

Tenstorrent is seeking a TT-Distributed Software Engineer to develop and optimize distributed software systems for high-performance AI and HPC clusters. The role focuses on distributed programming across multiple nodes, systems programming, inter-node communication, and scalable architectures to advance distributed inference and training infrastructure. The position is hybrid and based in Santa Clara, California; Austin, Texas; or Toronto, Ontario. Candidates at various experience levels are welcome; the appropriate level will be assessed during interviews and offers will align with that level.

The engineer will build compiler and systems software that enables AI workloads to run efficiently across accelerators and compute nodes. Work includes workload partitioning, graph transformation, scheduling, parallel execution, communication optimization, and runtime interfaces connecting compiler-generated plans to hardware and communication infrastructure. The role also involves profiling, benchmarking, and debugging distributed workloads in collaboration with compiler, runtime, architecture, and AI software teams.

Compensation ranges from $100,000 to $500,000, including base and variable compensation targets. Actual offers depend on experience, skills, education, background, and location. Employment is contingent on eligibility to access U.S. export-controlled technology and may depend on citizenship, permanent residency, or obtaining prior license approval.

Requirements

• Strong C++ or systems software engineering skills.
• A solid foundation in compiler design, programming languages, or performance-oriented systems programming.
• Ability to reason about data movement, communication overhead, synchronization, and performance tradeoffs across multiple compute devices and nodes.
• Experience in or willingness to work with distributed execution, parallel programming models, and large-scale AI workloads.
• First-principles problem-solving skills, including profiling complex systems, identifying bottlenecks, and translating performance insights into software optimizations.

Nice To Haves

• Interest in compiler optimizations, computation graphs, parallel execution, and mapping workloads onto heterogeneous or distributed hardware.

Responsibilities

• Design, implement, and optimize compiler and systems software that enables AI workloads to execute efficiently across multiple accelerators and compute nodes.
• Develop techniques for workload partitioning, graph transformation, scheduling, and parallel execution across distributed hardware.
• Optimize communication and computation together, including collective operations, synchronization, data movement, and communication-aware execution strategies.
• Build and improve distributed programming abstractions and runtime interfaces connecting compiler-generated execution plans with underlying hardware and communication infrastructure.
• Profile, benchmark, and debug distributed workloads to identify performance bottlenecks and validate optimizations.
• Collaborate with compiler, runtime, architecture, and AI software teams.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed