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Direct message the job poster from Annapurna
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
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Mid-Senior level
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Full-time
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Staffing and Recruiting
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#J-18808-Ljbffr”, “datePosted”: “2026-04-11”, “hiringOrganization”: { “@type”: “Organization”, “name”: “Annapurna”, “sameAs”: “https://uk.whatjobs.com/pub_api__cpl__402718910__4861?utm_campaign=publisher&utm_medium=api&utm_source=4861&geoID=33” }, “jobLocation”: { “@type”: “Place”, “address”: { “@type”: “PostalAddress”, “addressLocality”: “London” } } }Get AI-powered advice on this job and more exclusive features.
Direct message the job poster from Annapurna
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
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Industries
Staffing and Recruiting
Referrals increase your chances of interviewing at Annapurna by 2x
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We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
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