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Staff Backend Software Engineer - GO & Python
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Detalles
- Tipo de emprego
- Xornada completa
- Mando a distancia
- Non
- Empresa
- Physicsx
Descrición
About us
Re-architecting Engineering for the Age of Intelligence
PhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London, New York, and Singapore and an expanding presence in the Bay Area.
The Role
PhysicsX is building a platform that enables Data Scientists and Simulation Engineers to build, train, and deploy Deep Physics Models. The platform handles massive volumes of complex simulation data and enables high fidelity multi physics simulation through AI inference.
We are looking for a Senior (potentially Staff level, depending on the candidate) Software Engineer to join the AI Workbench platform team. This is a software engineering role, not an ML research role. You do not need to be a practising ML engineer, but you do need to be fluent in the language of ML and data platforms, ideally through prior hands on experience with ML platforms or data science work.
The team sits in a highly infrastructure heavy domain without being an infrastructure team itself. A large part of the role is building strong working relationships with the infrastructure team and owning the work that falls in the space between the two, where ownership is not always clearly defined. You will also play a key role in mentoring and developing engineers across the team, some of whom are early career and some mid career.
Note for candidates: PhysicsX is currently going through a team reorganisation. The scope of this role may evolve as team structures settle, and we have kept this description intentionally broad rather than narrowly tailored to today's team shape.
What You Will Do
• Design and build distributed systems, services, and APIs for high dimensional simulation data across the machine learning lifecycle, from data processing and model training to inference services.
• Own work end to end in a domain where responsibilities often sit between the AIWB platform team and the wider infrastructure team, and proactively build the relationships needed to manage that ambiguity well.
• Build tools that enable data scientists and engineers to create automated, robust pipelines for data ingestion and processing, powering active learning loops.
• Architect and integrate storage solutions, data warehouses, and data lakes to handle the demands of complex simulations, multimodal data, and deep learning workloads.
• Deploy and support services across more than one production environment, including cloud and on premises or air gapped customer environments.
• Define system architecture for new capabilities, making trade offs across performance, reliability, cost, and developer experience.
• Author and review Technical Decision Records and contribute to Technology Radar reviews.
• Mentor and support the growth of engineers across the team, including those earlier in their careers, and act as a technical role model.
• Remain genuinely hands on. Writing code stays part of the job at every level, this is not a purely managerial track.
• Communicate clearly and confidently with a wide range of stakeholders and personalities across engineering, delivery, and customer facing teams.
What You Bring to the Table
• A passion for the craft. You are driven by engineering excellence and enjoy building things properly, not just shipping quickly.
• Strong Kubernetes experience. This is a must have, including comfort with CRDs, Operators, and infrastructure configuration tools such as Helm or ArgoCD.
• Strong command of Go, plus working knowledge of Python. Comfort with Rust is also valued. Experience across Kubernetes, Go, Python, and Rust is ideal.
• Experience deploying and supporting services in more than one production environment, not just a single deployment target.
• An ML platform background or prior data science experience, even if you have since moved into pure software engineering. You understand how ML practitioners and researchers think and talk about problems.
• Intellectual curiosity and a proactive approach. You do not need to be told what to do next.
• Strong communication and organisational skills, with experience operating at a senior or staff level, or equivalent people leadership experience, in a comparable engineering organisation.
• Comfort with ambiguity and an adaptable, startup minded approach. PhysicsX moves quickly and priorities shift, and we are looking for people who thrive in that environment rather than finding it difficult.
• Prior experience mentoring or developing other engineers.
Ideally
• Experience at an ML focused startup or platform company, or a strong infrastructure background from a larger organisation such as a bank, provided you can demonstrate adaptability to a smaller, faster moving environment
• Side projects, open source contributions, or things you have built for their own sake. Not a requirement, but a nice signal of genuine engineering passion.
• Understanding of what it takes to build and support software across cloud, on premises, and air gapped environments.
• Experience with big data systems and analytics at scale in production.
What We Offer
• Equity options, share in our success and growth.
• 10% employer pension contribution, invest in your future.
• Free office lunches, great food to fuel your workdays.
• Flexible working, balance your work and life in a way that works for you.…
Source: Arbeitnow (https://www.arbeitnow.co.uk/jobs/companies/physicsx/staff-backend-software-engineer-go-python-london-190227)
Re-architecting Engineering for the Age of Intelligence
PhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London, New York, and Singapore and an expanding presence in the Bay Area.
The Role
PhysicsX is building a platform that enables Data Scientists and Simulation Engineers to build, train, and deploy Deep Physics Models. The platform handles massive volumes of complex simulation data and enables high fidelity multi physics simulation through AI inference.
We are looking for a Senior (potentially Staff level, depending on the candidate) Software Engineer to join the AI Workbench platform team. This is a software engineering role, not an ML research role. You do not need to be a practising ML engineer, but you do need to be fluent in the language of ML and data platforms, ideally through prior hands on experience with ML platforms or data science work.
The team sits in a highly infrastructure heavy domain without being an infrastructure team itself. A large part of the role is building strong working relationships with the infrastructure team and owning the work that falls in the space between the two, where ownership is not always clearly defined. You will also play a key role in mentoring and developing engineers across the team, some of whom are early career and some mid career.
Note for candidates: PhysicsX is currently going through a team reorganisation. The scope of this role may evolve as team structures settle, and we have kept this description intentionally broad rather than narrowly tailored to today's team shape.
What You Will Do
• Design and build distributed systems, services, and APIs for high dimensional simulation data across the machine learning lifecycle, from data processing and model training to inference services.
• Own work end to end in a domain where responsibilities often sit between the AIWB platform team and the wider infrastructure team, and proactively build the relationships needed to manage that ambiguity well.
• Build tools that enable data scientists and engineers to create automated, robust pipelines for data ingestion and processing, powering active learning loops.
• Architect and integrate storage solutions, data warehouses, and data lakes to handle the demands of complex simulations, multimodal data, and deep learning workloads.
• Deploy and support services across more than one production environment, including cloud and on premises or air gapped customer environments.
• Define system architecture for new capabilities, making trade offs across performance, reliability, cost, and developer experience.
• Author and review Technical Decision Records and contribute to Technology Radar reviews.
• Mentor and support the growth of engineers across the team, including those earlier in their careers, and act as a technical role model.
• Remain genuinely hands on. Writing code stays part of the job at every level, this is not a purely managerial track.
• Communicate clearly and confidently with a wide range of stakeholders and personalities across engineering, delivery, and customer facing teams.
What You Bring to the Table
• A passion for the craft. You are driven by engineering excellence and enjoy building things properly, not just shipping quickly.
• Strong Kubernetes experience. This is a must have, including comfort with CRDs, Operators, and infrastructure configuration tools such as Helm or ArgoCD.
• Strong command of Go, plus working knowledge of Python. Comfort with Rust is also valued. Experience across Kubernetes, Go, Python, and Rust is ideal.
• Experience deploying and supporting services in more than one production environment, not just a single deployment target.
• An ML platform background or prior data science experience, even if you have since moved into pure software engineering. You understand how ML practitioners and researchers think and talk about problems.
• Intellectual curiosity and a proactive approach. You do not need to be told what to do next.
• Strong communication and organisational skills, with experience operating at a senior or staff level, or equivalent people leadership experience, in a comparable engineering organisation.
• Comfort with ambiguity and an adaptable, startup minded approach. PhysicsX moves quickly and priorities shift, and we are looking for people who thrive in that environment rather than finding it difficult.
• Prior experience mentoring or developing other engineers.
Ideally
• Experience at an ML focused startup or platform company, or a strong infrastructure background from a larger organisation such as a bank, provided you can demonstrate adaptability to a smaller, faster moving environment
• Side projects, open source contributions, or things you have built for their own sake. Not a requirement, but a nice signal of genuine engineering passion.
• Understanding of what it takes to build and support software across cloud, on premises, and air gapped environments.
• Experience with big data systems and analytics at scale in production.
What We Offer
• Equity options, share in our success and growth.
• 10% employer pension contribution, invest in your future.
• Free office lunches, great food to fuel your workdays.
• Flexible working, balance your work and life in a way that works for you.…
Source: Arbeitnow (https://www.arbeitnow.co.uk/jobs/companies/physicsx/staff-backend-software-engineer-go-python-london-190227)
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Orixe: Physicsx
Localización
Londres, Reino Unido
Ficha proporcionada por Physicsx.
