Tech Lead – AI Compiler

Darwin Recruitment; San Francisco (CA); On-site; USD 180,000 - 300,000; Full time

Job summary

Darwin Recruitment is seeking a Technical Lead to drive the design and development of compiler technologies for AI workloads in San Francisco. This hands-on role blends advanced C++ engineering with architectural leadership to optimize performance across software and hardware platforms.

You will mentor engineers, own complex projects from design through deployment, and collaborate with hardware, runtime and ML teams to push computing capabilities and deliver high-performance software.

Qualifications

• 8+ years of software engineering in systems software or compilers.
• Strong C++ and understanding of data structures and software architecture.
• Experience leading complex technical projects and mentoring engineers.

Responsibilities

• Lead architecture and development of compiler infrastructure for AI workloads.
• Design and optimize compiler transformations and code generation.
• Improve performance with fusion, scheduling, memory optimizations.
• Own projects from design to testing and deployment.
• Collaborate with hardware, runtime and ML teams on system capabilities.
• Mentor engineers and conduct technical reviews.
• Drive planning and delivery across multiple teams.

Skills

8+ years exp

C++

Data structures

Software architecture

Leadership

Education

BSc/MSc in CS/CE

Tools

LLVM

MLIR

XLA

TVM

Job description

Job Title: Technical Lead – AI Compiler Engineering

Location: San Francisco
Salary: Competitive, dependent on experience
Industry: AI Software and Computing Infrastructure

Overview of the Role

We are working with a technology business developing software infrastructure to improve the performance and efficiency of advanced computing systems.

They are looking to hire a Technical Lead to drive the design and development of compiler technologies and performance-critical software for AI and machine learning workloads.

This role combines hands-on C++ engineering, architectural decision-making and technical leadership. You will work closely with software, systems and hardware engineers to optimise workloads, enable new computing capabilities and deliver reliable, high-performance software.

Key Responsibilities

• Lead the architecture and development of compiler infrastructure and software components for AI workloads.
• Design and optimise compiler transformations, intermediate representations, code generation and execution pipelines.
• Improve performance through operation fusion, workload scheduling, memory optimisation and hardware-specific techniques.
• Own complex engineering projects from design through implementation, testing and deployment.
• Collaborate with hardware, runtime and machine learning teams to improve system capabilities and workload performance.
• Debug complex functional, integration and performance issues across software and hardware layers.
• Establish engineering best practices, lead technical reviews and mentor engineers.
• Drive technical planning and delivery across multiple contributors and engineering teams.

Candidate Profile

Essential

• 8+ years of software engineering experience in systems software, compilers, computing infrastructure or performance-critical applications.
• Bachelor’s or master’s degree in computer science, Computer Engineering or a related field, or equivalent practical experience.
• Strong C++ programming skills and knowledge of data structures, algorithms and software architecture.
• Technical expertise in at least one of the following: compiler design, operating systems, computer architecture, high-performance computing or accelerator software.
• Proven experience leading complex technical projects from design through implementation and delivery.
• Experience providing technical leadership, mentoring engineers and making architectural decisions.

Highly Preferred

• Experience with compiler frameworks such as LLVM, MLIR, XLA, TVM or similar technologies.
• Knowledge of compiler optimisation, intermediate representations, lowering pipelines or code generation.
• Familiarity with machine learning frameworks such as PyTorch or TensorFlow, or model formats such as ONNX.
• Experience with GPUs, NPUs, custom accelerators, parallel computing or heterogeneous systems.

Beneficial

• Experience with performance profiling, benchmarking and regression testing.
• Knowledge of memory management, operator fusion, scheduling and hardware-specific optimisation.
• Experience leading cross-functional engineering initiatives and improving software development practices.