Engineering Manager, GPU Kernel Job at Wayve (London)

New

Senior Product Manager

We are hiring a foundational Product Manager to work directly with the CTO to de...

Location

Israel , Ramat Gan

Salary:

Not provided

SQream

Expiration Date

Until further notice

Requirements

5+ years of experience as a Product Manager or Solutions Architect in infrastructure, HPC, data systems, GPU/AI pipelines, or distributed systems
Strong outbound / customer-facing skills: presenting to CTOs, architects, OEM teams, GSIs, and technical buyers
Ability to operate at kernel-level conceptual depth and translate physics into product strategy
Exceptional communication skills - written and verbal - with the ability to simplify complex GPU and dataflow concepts
Demonstrated ability to drive roadmap execution with engineering while also leading external discovery and evangelism
Comfort owning both internal product discipline and external technical influence

Job Responsibility

Product Ownership (Internal): Work directly with the R&D to shape the GPU-native roadmap for ingestion, vectorization, transformation, curation, and continuous production flow
Define precise specifications, APIs, pipeline behavior, and physics-aligned constraints
Ensure product features adhere to SCAILIUM’s rigid boundaries: No orchestration. No system of record. No serving. No dashboards
Enforce documentation rigor. Documentation is code
Technical Outbound Leadership (External): Serve as a public-facing authority on GPU starvation, impedance incompatibility, and the AI Production Layer
Lead technical sessions with Partners, OEMs (Dell, Supermicro, HPE), GSIs (Accenture, Deloitte), and strategic enterprise customers
Conduct in-depth customer pipeline analyses to identify physical constraints and translate them into SCAILIUM features or patterns
Present SCAILIUM’s architecture in a clear, authoritative, physics-grounded manner
Support sales, partnerships, and field engineering by communicating the “why” behind every product decision
Build artifacts that shape the category: reference architectures, workload blueprints, TCO models, and silicon saturation narratives

Autonomy Engineer - Deep Learning Infrastructure

Skydio is the leading US drone company and the world leader in autonomous flight...

Location

United States , San Mateo

Salary:

170000.00 - 236500.00 USD / Year

Skydio

Expiration Date

Until further notice

Requirements

Demonstrated hands-on experience with MLOps, ML inference optimization and edge deployment
Strong knowledge of DL fundamentals, techniques and state-of-the-art DL models/architectures
Strong fundamentals in CV, image processing and video processing
Demonstrated hands-on experience building and managing ML pipelines for solving vision or vision language tasks including data preparation, model training, model deployment and monitoring
Experience and understanding of security and compliance requirements in ML infrastructure
Experience with ML frameworks and libraries
Demonstrated ability to take a concept and systematically drive it through the software lifecycle: architecture, development, testing, and deployment, and monitoring
Comfortable navigating and delivering within a complex codebase
Strong communication skills and the ability to collaborate effectively at all levels of technical depth

Job Responsibility

Develop solutions for high-performance deep learning inference for CV workloads that can deliver high throughput and low latency on different hardware platforms
Profile CV and Vision Language Models (VLMs) to analyze performance, identify bottlenecks and optimization opportunities and improve power efficiency of deep learning inference workloads
Design and implement end to end MLOps workflows for model deployment, monitoring and re-training
Utilize advanced Machine Learning knowledge to leverage training or runtime frameworks or model efficiency tools to improve system performance
Create new methods for improving training efficiency
Implement GPU kernels for custom architectures and optimized inference
Design and implement SDKs that allow customers/external developers to create autonomous workflows using ML
Leverage your expertise and best-practices to uphold and improve Skydio’s engineering standards

What we offer

Equity in the form of stock options
Comprehensive benefits packages
Relocation assistance may also be provided for eligible roles
Paid vacation time
Sick leave
Holiday pay
401K savings plan

Fulltime

Autonomy Engineer - Deep Learning Infrastructure

Learning a semantic and geometric understanding of the world from visual data is...

Location

Switzerland , Zurich

Salary:

Not provided

Skydio

Expiration Date

Until further notice

Requirements

Demonstrated hands-on experience with MLOps, ML inference acceleration/optimization, and edge deployment
Strong knowledge of DL fundamentals, techniques, and state-of-the-art DL models/architectures
Strong fundamentals in CV, image processing, and video processing
Demonstrated hands-on experience building and managing ML pipelines for solving vision or vision language tasks including data preparation, model training, model deployment, and monitoring
Experience and understanding of security and compliance requirements in ML infrastructure
Experience with ML frameworks and libraries
Demonstrated ability to take a concept and systematically drive it through the software lifecycle: architecture, development, testing, and deployment, and monitoring
Comfortable navigating and delivering within a complex codebase
Strong communication skills and the ability to collaborate effectively at all levels of technical depth

Job Responsibility

Develop solutions for high-performance deep learning inference for CV workloads that can deliver high throughput and low latency on different hardware platforms
Profile CV and Vision Language Models (VLMs) to analyze performance, identify bottlenecks and acceleration/optimization opportunities and improve power efficiency of deep learning inference workloads
Design and implement end to end MLOps workflows for model deployment, monitoring, and re-training
Utilize advanced Machine Learning knowledge to leverage training or runtime frameworks or model efficiency tools to improve system performance
Create new methods for improving training efficiency
Implement GPU kernels for custom architectures and optimized inference
Design and implement SDKs that allow customers/external developers to create autonomous workflows using Machine Learning (ML)
Leverage your expertise and best-practices to uphold and improve Skydio’s engineering standards

What we offer

Equity in the form of stock options
Comprehensive benefits packages
Relocation assistance may also be provided for eligible roles
Group health insurance plans
Paid vacation time
Sick leave
Holiday pay
401K savings plan

Fulltime

Autonomy Engineer - Deep Learning Model Acceleration

Learning a semantic and geometric understanding of the world from visual data is...

Location

United States , San Mateo, California

Salary:

170000.00 - 277500.00 USD / Year

Skydio

Expiration Date

Until further notice

Requirements

Demonstrated hands-on experience with MLOps, ML inference acceleration/optimization, and edge deployment
Strong knowledge of DL fundamentals, techniques, and state-of-the-art DL models/architectures
Strong fundamentals in CV, image processing, and video processing
Demonstrated hands-on experience building and managing ML pipelines for solving vision or vision language tasks including data preparation, model training, model deployment, and monitoring
Experience and understanding of security and compliance requirements in ML infrastructure
Experience with ML frameworks and libraries
Demonstrated ability to take a concept and systematically drive it through the software lifecycle: architecture, development, testing, and deployment, and monitoring
Comfortable navigating and delivering within a complex codebase
Strong communication skills and the ability to collaborate effectively at all levels of technical depth

Job Responsibility

Develop solutions for high-performance deep learning inference for CV workloads that can deliver high throughput and low latency on different hardware platforms
Profile CV and Vision Language Models (VLMs) to analyze performance, identify bottlenecks and acceleration/optimization opportunities and improve power efficiency of deep learning inference workloads
Design and implement end to end MLOps workflows for model deployment, monitoring, and re-training
Utilize advanced Machine Learning knowledge to leverage training or runtime frameworks or model efficiency tools to improve system performance
Create new methods for improving training efficiency
Implement GPU kernels for custom architectures and optimized inference
Design and implement SDKs that allow customers/external developers to create autonomous workflows using Machine Learning (ML)
Leverage your expertise and best-practices to uphold and improve Skydio’s engineering standards

What we offer

Equity in the form of stock options
Comprehensive benefits packages
Relocation assistance may also be provided for eligible roles
Paid vacation time
Sick leave
Holiday pay
401K savings plan
Group health insurance plans

Fulltime

Autonomy Engineer - Deep Learning Model Acceleration

Learning a semantic and geometric understanding of the world from visual data is...

Location

Switzerland , Zurich

Salary:

Not provided

Skydio

Expiration Date

Until further notice

Requirements

Demonstrated hands-on experience with MLOps, ML inference acceleration/optimization, and edge deployment
Strong knowledge of DL fundamentals, techniques, and state-of-the-art DL models/architectures
Strong fundamentals in CV, image processing, and video processing
Demonstrated hands-on experience building and managing ML pipelines for solving vision or vision language tasks including data preparation, model training, model deployment, and monitoring
Experience and understanding of security and compliance requirements in ML infrastructure
Experience with ML frameworks and libraries
Demonstrated ability to take a concept and systematically drive it through the software lifecycle: architecture, development, testing, and deployment, and monitoring
Comfortable navigating and delivering within a complex codebase
Strong communication skills and the ability to collaborate effectively at all levels of technical depth

Job Responsibility

Develop solutions for high-performance deep learning inference for CV workloads that can deliver high throughput and low latency on different hardware platforms
Profile CV and Vision Language Models (VLMs) to analyze performance, identify bottlenecks and acceleration/optimization opportunities and improve power efficiency of deep learning inference workloads
Design and implement end to end MLOps workflows for model deployment, monitoring, and re-training
Utilize advanced Machine Learning knowledge to leverage training or runtime frameworks or model efficiency tools to improve system performance
Create new methods for improving training efficiency
Implement GPU kernels for custom architectures and optimized inference
Design and implement SDKs that allow customers/external developers to create autonomous workflows using Machine Learning (ML)
Leverage your expertise and best-practices to uphold and improve Skydio’s engineering standards

What we offer

Competitive base salaries
Equity in the form of stock options
Comprehensive benefits packages
Relocation assistance may also be provided for eligible roles
Paid vacation time
Sick leave
Holiday pay
Retirement savings plan

Fulltime

Autonomy Engineer - Deep Learning Infrastructure

Learning a semantic and geometric understanding of the world from visual data is...

Location

United States , San Mateo, California

Salary:

170000.00 - 277500.00 USD / Year

Skydio

Expiration Date

Until further notice

Requirements

Demonstrated hands-on experience with MLOps, ML inference acceleration/optimization, and edge deployment
Strong knowledge of DL fundamentals, techniques, and state-of-the-art DL models/architectures
Strong fundamentals in CV, image processing, and video processing
Demonstrated hands-on experience building and managing ML pipelines for solving vision or vision language tasks including data preparation, model training, model deployment, and monitoring
Experience and understanding of security and compliance requirements in ML infrastructure
Experience with ML frameworks and libraries
Demonstrated ability to take a concept and systematically drive it through the software lifecycle: architecture, development, testing, and deployment, and monitoring
Comfortable navigating and delivering within a complex codebase
Strong communication skills and the ability to collaborate effectively at all levels of technical depth

Job Responsibility

Develop solutions for high-performance deep learning inference for CV workloads that can deliver high throughput and low latency on different hardware platforms
Profile CV and Vision Language Models (VLMs) to analyze performance, identify bottlenecks and acceleration/optimization opportunities and improve power efficiency of deep learning inference workloads
Design and implement end to end MLOps workflows for model deployment, monitoring, and re-training
Utilize advanced Machine Learning knowledge to leverage training or runtime frameworks or model efficiency tools to improve system performance
Create new methods for improving training efficiency
Implement GPU kernels for custom architectures and optimized inference
Design and implement SDKs that allow customers/external developers to create autonomous workflows using Machine Learning (ML)
Leverage your expertise and best-practices to uphold and improve Skydio’s engineering standards

What we offer

Equity in the form of stock options
Comprehensive benefits packages
Relocation assistance may also be provided for eligible roles
Paid vacation time, sick leave, holiday pay and 401K savings plan

Fulltime

Autonomy Engineer - Deep Learning Model Acceleration

Learning a semantic and geometric understanding of the world from visual data is...

Location

Switzerland , Zurich

Salary:

Not provided

Skydio

Expiration Date

Until further notice

Requirements

Demonstrated hands-on experience with MLOps, ML inference acceleration/optimization, and edge deployment
Strong knowledge of DL fundamentals, techniques, and state-of-the-art DL models/architectures
Strong fundamentals in CV, image processing, and video processing
Demonstrated hands-on experience building and managing ML pipelines for solving vision or vision language tasks including data preparation, model training, model deployment, and monitoring
Experience and understanding of security and compliance requirements in ML infrastructure
Experience with ML frameworks and libraries
Demonstrated ability to take a concept and systematically drive it through the software lifecycle: architecture, development, testing, deployment, and monitoring
Comfortable navigating and delivering within a complex codebase
Strong communication skills and the ability to collaborate effectively at all levels of technical depth

Job Responsibility

Develop solutions for high-performance deep learning inference for CV workloads that can deliver high throughput and low latency on different hardware platforms
Profile CV and Vision Language Models (VLMs) to analyze performance, identify bottlenecks and acceleration/optimization opportunities and improve power efficiency of deep learning inference workloads
Design and implement end to end MLOps workflows for model deployment, monitoring, and re-training
Utilize advanced Machine Learning knowledge to leverage training or runtime frameworks or model efficiency tools to improve system performance
Create new methods for improving training efficiency
Implement GPU kernels for custom architectures and optimized inference
Design and implement SDKs that allow customers/external developers to create autonomous workflows using Machine Learning (ML)
Leverage your expertise and best-practices to uphold and improve Skydio’s engineering standards

What we offer

Competitive base salaries
Equity in the form of stock options
Comprehensive benefits packages
Relocation assistance may also be provided for eligible roles
Group health insurance plans
Paid vacation time
Sick leave
Holiday pay
Retirement savings plan

Fulltime

Senior Devops & AI Engineer

This role presents a unique opportunity to contribute to the future of impactful...

Location

India , Hyderabad

Salary:

Not provided

Fission Labs

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Engineering, or related field
6+ years of experience in Infrastructure Mgmt. roles, with a focus on cloud platforms (Azure and AWS Preferred)
Hands-on experience with operations (DevSecOps) principles and best practices
Proficiency in scripting languages such as Python, PowerShell, or Bash
Excellent communication and collaboration skills
In-depth knowledge of Linux operating systems, including CentOS, Ubuntu, and Red Hat, with expertise in shell scripting, package management, and system administration
Hands-on experience with a wide range of AWS and Azure services
Develop and maintain Infrastructure as Code (IAC) templates using tools such as Terraform or AWS CloudFormation
Experience setting up cloud infrastructure stack, databases, service endpoints, GPU as well as CPU resource scaling, optimization etc.
Should have worked AIOps/MLOP

Job Responsibility

Configure and optimize Linux-based servers for performance, security, and resource utilization, including kernel tuning, file system management, and network configuration
Architect cloud solutions leveraging best practices and services offered by AWS and Azure, optimizing for scalability, reliability, and cost-effectiveness
Implement and manage hybrid cloud environments, facilitating seamless integration and interoperability between AWS and Azure services
Establish version control practices for IAC templates, ensuring traceability, auditability, and reproducibility of infrastructure changes

What we offer

Opportunity to work on impactful technical challenges with global reach
Vast opportunities for self-development, including online university access and knowledge sharing opportunities
Sponsored Tech Talks & Hackathons to foster innovation and learning
Generous benefits packages including health insurance, retirement benefits, flexible work hours, and more
Supportive work environment with forums to explore passions beyond work

Fulltime

Engineering Manager, GPU Kernel

Wayve

Location:
United Kingdom , London

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
January 01, 2026

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