Senior Machine Learning Engineer
- Discuss this with your agent
- Open in Claude
- Open in ChatGPT
Role details
Tech stack
+4 more
Job description
- Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization & control) to customer production environments.
- Communicate results and trade-offs to senior stakeholders; steer roadmaps and influence product direction with evidence.
- Lead scoping and architecture design for data/ML systems; define success metrics, delivery plans and quality bars.
- Excel at building robust and scalable ML systems, training and inference pipelines and APIs, running both on cloud and on-prem environments. The tech stack you will use for this includes: Python, PyTorch, Pandas, fastAPI, Scipy, Kubeflow, among others.
- Mentor and develop engineers and data scientists; provide technical direction and clear, calm decision-making under pressure.
- Travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where youâll collaborate closely with customers to build solutions on-site.
- Own the scoping of new projects and work-streams with existing customers and taking part in bringing new customers to PhysicsX.
As a senior member of the team, youâll significantly influence our technical direction and will be involved in shaping future solutions and products, while developing your skills as a technical leader.
Requirements
As a Senior Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.
Youâve shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools and make pragmatic product decisions that set Delivery up for success. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.
With at least 3 years industry experience (post Masters or PhD) in a commercial, non-research environment, youâre ready to not only execute but also lead and mentor others. Youâre truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.
As a Senior MLE, youâll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes.
About the company
Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.
Learn alongside exceptional people
Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If youâre ambitious, thoughtful, and driven by impact, youâll feel at home.
Influence over hierarchy
We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isnât just welcomed, itâs expected.
Sustainable pace, long-term ambition
Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.
And it doesnât stop there âŚ
Equity options - share meaningfully in the company youâre helping to build.
10% employer pension contribution - because investing in future matters.
ď¸ Free office lunches - to keep you energised and focused.
Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.
YellowNest nursery scheme - to help working parents manage childcare costs.
ď¸ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.
Private medical insurance - 100% employee cover, giving you complete peace of mind.
Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.
Eye tests - because good work depends on good health.
Personal development - dedicated support for learning, development, and leveling up over time.
Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.
Bike2Work scheme and Season ticket loan - to make getting to work easier and greener.
Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.
Watch this space, weâre continuing to build this as we growâŚ
Apply for this position
This job is hosted externally. Click below to view the full posting and apply.
Apply on www.adzuna.co.ukGood distractions
Talks and stories from around this role â technically off-topic, practically not.
Moments
Explore playlistsVideos
See allRelated articles
See all
MLops â Deploying, Maintaining And Evolving Machine Learning Models in Production
Data Engineer Salary UK
MLOps â Whatâs the deal behind it?
Why Upskilling And Reskilling is Important For Developers