PyTorch Engineer

Graphcore

ABOUT GRAPHCORE  Graphcore is one of the world’s leading innovators in Artificial Intelligence compute.   It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry.   As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone.    Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation.   JOB SUMMARY   Reporting to a Team Lead in the frameworks team you will play a pivotal role in designing, implementing, optimising, maintaining and supporting the software required to ensure the machine learning accelerators that Graphcore develop, enjoy first-class support in state-of-the-art machine learning frameworks such as PyTorch and Triton.   This role sees you joining our PyTorch team, where you will be part of a SCRUM team working on delivering new features, optimise performance, reviewing code changes, writing technical documentation, working with upstream communities, maintaining the code base and supporting users.   In this role you will closely collaborate with other engineers, both within the PyTorch team as well as other engineering teams. You help the team coordinate and deliver complex, open-ended technical tasks. You are pro-active and an excellent communicator. You will develop deep expertise in the PyTorch project and will (in time) contribute to the team’s technical direction and processes. You understand the importance of managing code quality and code complexity and balancing this against the need to deliver business outcomes.  Note that the job title and associated benefits will be tailored to the successful candidate’s level of experience at the job offer stage to one of Software Engineer, Staff Engineer, Senior Staff Engineer, Principal Software Engineer or Senior Principal Software Engineer.   Note that as the machine learning software landscape is quite fast moving and as such flexibility is essential – over time you may be asked to work on frameworks other than PyTorch.  THE TEAM  The Frameworks team ensures Graphcore hardware works seamlessly with the tools that ML engineers and researchers love – Pytorch, Triton, Jax and TensorFlow. We’re a talented and diverse team of engineers and we foster a culture of collaboration, openness and learning. All our software teams follow agile working practices, and we care deeply about both ease-of-use as well as performance. We work closely work with other Graphcore teams as well as leading open-source communities.  By joining us, you’ll join our exciting journey on the cutting edge of the machine learning industry. Your contributions will make a real difference – enabling machine learning engineers and researchers to unlock the full potential of Graphcore’s hardware.   RESPONSIBILITIES AND DUTIES  * Designing and implementing new features & maintaining and supporting existing features. * Developing and maintaining unit tests, component tests and integration tests. * Optimising the software stack to make it more performant for our users. * Managing complex technical tasks with cross-team dependencies. * Managing code quality, code complexity and technical debt. * Provide technical leadership, contributing the team’s technical direction and processes. * Contributing to documentation, including user manuals and tutorials. * Conducting code reviews. * Resolving regressions, performance issues and software defects. * Coaching and mentoring other team members. * Contributing to a collaborative team culture. * Contribute to continuous improvements to improve ways of working. * Working with upstream open-source development teams. CANDIDATE PROFILE  Essential:  * Demonstrable strong software engineering skills. * Experience of Python development. * Experience of developing performant C++ applications in a commercial setting. At least one of: * Experience of writing ML kernels. * Experience of compiler development. * Experience of using and/or development of ML Frameworks. * Experience in a computationally intensive engineering field. Desirable:  * Demonstrable knowledge of AI/ML. * Understanding of computing architectures. * Experience of maintaining and supporting a complex code base. * Experience in profiling / optimising high performance code. BENEFITS In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments. Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

Harmattan AI

ABOUT US Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces. Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected. ABOUT THE ROLE As a Machine Learning Engineer on our Foundational team in Paris, you will build the "brain" of our tactical robots. You will design and scale large-scale, multi-modal foundational models that learn robust representations of the battlefield using Self-Supervised Learning (SSL) from massive amounts of unlabelled Electro-Optical (EO) and Infrared (IR) data. Your work provides the critical foundational weights that our Edge AI team distills into hyper-accurate models running on tactical hardware.   RESPONSIBILITIES * Multi-Modal SSL Architecture Design: Design neural network architectures (Vision Transformers) and loss functions (Masked Autoencoders, Contrastive Learning) to jointly learn from paired and unpaired EO and IR data. * Distributed Training Infrastructure: Manage and optimise training pipelines across multi-node GPU clusters, handling mixed-precision training and data loading. * Representation Evaluation: Develop metrics and linear-probing benchmarks to prove the latent space captures useful semantic features before distillation. * Data Strategy: Audit existing EO/IR data lakes and implement cross-attention mechanisms to fuse diverse sensor features. * Cross-Functional Collaboration: Sync with Data Engineers on ingestion pipelines and collaborate with the Edge AI team to ensure high-performance model handoffs. Candidate Requirements * Educational Background: A PhD or a highly research-focused MS in Computer Science, Machine Learning, Computer Vision, or Applied Mathematics. * Proven Experience: Minimum of 5-6 years of experience for senior levels. Experience training and scaling deep learning vision models (ViTs, CNNs) from scratch in multi-GPU/multi-node environments. Successful application of novel SSL or multi-modal architectures (e.g., CLIP, MAE, DINO) to real-world, non-standard imaging data (IR, SAR, or hyperspectral). * Technical Proficiency: Hardcore PyTorch engineering skills combined with deep mathematical intuition for representation learning. Knowledge of system-level languages (C++, Rust, or Go) and resource optimisation for edge computing. * Complexity & Leadership: Ability to architect state machines for fault-tolerant data pipelines and mediate technical trade-offs between hardware and algorithm teams. * Commitment & Mindset: 100% dedication to Harmattan AI’s mission of providing an ethical defence edge to allied countries. A hybrid researcher-engineer mindset that treats data quality as seriously as algorithm design We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

Harmattan AI

ABOUT US Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces. Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected. ABOUT THE ROLE As a Machine Learning Engineer on our Foundational team in Paris, you will build the "brain" of our tactical robots. You will design and scale large-scale, multi-modal foundational models that learn robust representations of the battlefield using Self-Supervised Learning (SSL) from massive amounts of unlabelled Electro-Optical (EO) and Infrared (IR) data. Your work provides the critical foundational weights that our Edge AI team distills into hyper-accurate models running on tactical hardware.   RESPONSIBILITIES * Multi-Modal SSL Architecture Design: Design neural network architectures (Vision Transformers) and loss functions (Masked Autoencoders, Contrastive Learning) to jointly learn from paired and unpaired EO and IR data. * Distributed Training Infrastructure: Manage and optimise training pipelines across multi-node GPU clusters, handling mixed-precision training and data loading. * Representation Evaluation: Develop metrics and linear-probing benchmarks to prove the latent space captures useful semantic features before distillation. * Data Strategy: Audit existing EO/IR data lakes and implement cross-attention mechanisms to fuse diverse sensor features. * Cross-Functional Collaboration: Sync with Data Engineers on ingestion pipelines and collaborate with the Edge AI team to ensure high-performance model handoffs. Candidate Requirements * Educational Background: A PhD or a highly research-focused MS in Computer Science, Machine Learning, Computer Vision, or Applied Mathematics. * Proven Experience: Minimum of 5-6 years of experience for senior levels. Experience training and scaling deep learning vision models (ViTs, CNNs) from scratch in multi-GPU/multi-node environments. Successful application of novel SSL or multi-modal architectures (e.g., CLIP, MAE, DINO) to real-world, non-standard imaging data (IR, SAR, or hyperspectral). * Technical Proficiency: Hardcore PyTorch engineering skills combined with deep mathematical intuition for representation learning. Knowledge of system-level languages (C++, Rust, or Go) and resource optimisation for edge computing. * Complexity & Leadership: Ability to architect state machines for fault-tolerant data pipelines and mediate technical trade-offs between hardware and algorithm teams. * Commitment & Mindset: 100% dedication to Harmattan AI’s mission of providing an ethical defence edge to allied countries. A hybrid researcher-engineer mindset that treats data quality as seriously as algorithm design We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.