Engineering Manager

Annapurna; Greater London; Hybrid; GBP 144,000 - 176,000; Full time

Benefits offered by this job

Hybrid working policy

Opportunities for professional development

Inclusive work environment

Job summary

Annapurna Recruitment seeks an experienced Engineering Manager – GPU Kernel to lead a team optimizing machine learning workloads for embedded GPU environments. This London-based role offers hybrid working and the chance to work on cutting-edge AI deployment strategies.

Qualifications

• Experience as an Engineering Manager delivering complex engineering projects.
• Expertise in developing GPU kernels and/or ML compilers.

Responsibilities

• Lead a team of ML GPU kernel engineers for efficient ML deployments.
• Collaborate with technical leads on deployment strategies and frameworks.

Skills

Leadership

Communication

C++

Tools

CUDA

OpenCL

TensorRT

PyTorch

Job description

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Location: London based (Hybrid 2 days onsite)

Salary Range: Up to £160,000

Brief Summary

Annapurna Recruitment is seeking an experienced Engineering Manager – GPU Kernelto lead a high-impact team focused on optimizing machine learning (ML) workloads for embedded GPU environments. This London-based role offers the opportunity to work on cutting-edge AI deployment strategies for next-generation autonomous systems, with a hybrid working model.

What to Expect

The Engineering Manager will oversee a multidisciplinary team dedicated to developing custom GPU kernels and libraries that enhance the efficiency of transformer-based AI models on embedded GPUs and accelerators. Key responsibilities include:

• Leading and mentoring a team of ML GPU kernel engineers to ensure efficient ML deployments across a wide range of devices.
• Collaborating with technical leads to define foundational strategies for deployment frameworks, compilers, toolchains, and system-on-chips (SoCs).
• Setting clear objectives and priorities, and efficiently allocating resources to meet project goals.
• Engaging in cross-functional collaboration with ML engineers, software developers, and researchers to facilitate the deployment of end-to-end AI solutions at scale.
• Proven experience as an Engineering Manager delivering complex engineering projects.
• Expertise in developing GPU kernels and/or ML compilers (e.g., CUDA, OpenCL, TensorRT, MLIR, TVM).
• Experience optimizing systems to meet strict utilization and latency requirements.
• Excellent interpersonal and communication skills.
• Experience with C++ and ML frameworks such as PyTorch.
• Familiarity with ML deployment pipelines.
• Knowledge of embedded SoCs used in automotive environments (e.g., Nvidia, Qualcomm, Renesas).

The company offers a comprehensive benefits package, including:

• A hybrid working policy that combines in-office collaboration with remote flexibility.
• Opportunities to work on groundbreaking AI technologies with real-world applications.
• A supportive and inclusive work environment that values diversity and innovation.
• Access to ongoing professional development and career growth opportunities.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Industries

  Staffing and Recruiting

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