Machine Learning Engineer

Machine Learning Engineer

Orbital

Orbital is an AI-first industrial company building hardware from the atoms up. Our goal is to lead an industrial renaissance to advance critical technologies and secure our planet for generations to come. We’re starting with critical hardware for AI data centers to make them more performant and sustainable. Every Orbital product is invented with our AI platform — uniting AI-automated hardware engineering with AI-designed material science to achieve breakthrough real-world performance. We have an ambitious mission and need excellent people in all our teams - AI research, operations, advanced materials, mechanical engineering, chemical engineering and manufacturing. Working at Orbital means working in tightly integrated, vertically integrated teams. We’re looking for people who have a love of physical technology, curiosity in AI and a desire to learn. As a Machine Learning Engineer at Orbital, you will architect cutting-edge AI systems for the multi-scale design of physical technologies. When we say multi-scale, we mean it: we build world-class foundation models for simulating both the microscopic motion of atoms and the macroscopic flow of liquids in 1GW data centers. We then co-design across these different scales using the ingenuity of our scientists and engineers, augmented with best-in-class domain agents. In this role you will set exceptionally high technical standards and drive projects from prototype through to production deployment. First and foremost, we want to work with someone with a love of craftsmanship, continual learning, and building systems that scale. We also value low ego, and a genuine passion for using AI to solve major global industrial technology challenges. Key Responsibilities Set the technical bar and ensure engineering excellence * Establish and maintain exceptionally high standards for code quality, system architecture and ML research and engineering practices through hands-on coding and technical review * Design robust, well-engineered systems that others can build upon, balancing research velocity with production requirements * Drive technical decisions on model selection, training approaches and deployment strategies Deliver high-impact AI projects across diverse domains * Develop and deploy AI solutions across the entire technology development pipeline- computational chemistry simulations, agentic workflows and beyond * Rapidly upskill in new technical areas through close collaboration with domain experts (no prior chemistry or materials experience required) * Demonstrate strong implementation skills through hands-on development, contributing significantly to the codebase * Balance research rigour with pragmatic engineering to deliver production-ready systems at scale Push the frontier of ML research * Design and implement novel ML architectures for complex scientific domains, with work that meets publication standards at top-tier conferences * Drive research projects from conception through to deployment, showing initiative and technical depth * Engage continuously with the latest ML literature, staying current with developments in foundation models, generative AI and scientific machine learning What We're Looking For * Significant software engineering and ML experience, with depth in training, evaluating and deploying AI models - demonstrated through industry work * Proven experience training, evaluating and productionising AI models at scale, with deep understanding of the full ML lifecycle from research to deployment * Strong engineering fundamentals with the ability to write high-quality, maintainable code and architect robust systems * A strong ability to reason about algorithms, system design, linear algebra, probabilistic concepts and ML engineering trade-offs * An ability to debug complex machine learning systems through meticulous attention to detail, testing of edge cases and carefully selected ablations * A genuine interest in building AI systems that enable breakthrough scientific and industrial applications * Upon reading Hamming's You and Your Research, you resonate with quotes such as: * "Yes, I would like to do first-class work" * "You should do your job in such a fashion that others can build on top of it, so they will indeed say, 'Yes, I've stood on so and so's shoulders and I saw further.'" * "Instead of attacking isolated problems, I made the resolution that I would never again solve an isolated problem except as characteristic of a class" Bonus: Experience with physics-informed or chemistry-focused AI applications. Experience building or fine-tuning large language models. Experience with agent-based systems, tool use or agentic workflows. Contributions to open-source ML projects or published research. Orbital is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Machine Learning Engineer

Almedia

This isn’t your regular job. Almedia is a place where those who want to push harder can accelerate their careers faster than anywhere else. We’re aiming to become Germany’s second bootstrapped unicorn. Almedia is already Europe’s #3 fastest-growing company in 2025 (FT1000). We are building the future of marketing by rewarding our community of over 70 million users for engaging with our advertisers’ products. We are offering a new way to acquire users for the biggest companies in the world. MACHINE LEARNING ENGINEER £130K – £230K • Offers Equity You’ll take ownership of designing, developing, and scaling impactful, production-grade ML solutions that power Almedia’s products and growth. This is a hands-on role involving active participation in code development and delivery. TYPES OF PROBLEMS YOU’LL BE SOLVING * Designing and optimising user reward schemes based on player behaviour and market shifts * Leading the design and implementation of solutions for personalised, real-time reward values * Developing solutions for identifying underperforming reward campaigns and causes of failure YOUR ROLE * Lead end-to-end delivery: build, deploy, and optimise solutions and services at scale * Provide technical leadership across ML projects, ensuring best practices and high-quality code * Align technical capabilities with business priorities to unlock high-value opportunities * Apply advanced statistical and causal inference methods to ensure robustness and reliability * Partner with product and engineering teams to translate business challenges into predictive, data-driven solutions YOU HAVE * Proven expertise in building, deploying, and maintaining solutions and services in production, ideally in adtech or high-scale environments * Deep knowledge of statistics (A/B testing, regression, probability) * Strong programming background in Python and SQL, with hands-on cloud experience * Ability to mentor and set technical direction for ML engineers and cross-functional peers * Strong communication skills to influence both technical and non-technical stakeholders BONUS POINTS FOR * Passion for gaming and strong understanding of player behaviour * Experience with adtech, monetisation platforms, or the gambling industry * Familiarity with gaming KPIs such as pLTV, retention, and ROAS WHY ALMEDIA? * Scale With Almedia: Have a real impact and grow alongside a startup that has been profitable from day one. * High-Growth Environment: We encourage all staff to take ownership of projects and consistently raise the bar. * Do More, Get More: Generous bonus scheme to ensure great, proactive work is valued. We believe in fostering talent, evaluating all skill levels during the hiring process, and providing a clear path for growth. Almedia is an equal opportunity employer. We embrace and celebrate diversity, and encourage individuals from all backgrounds to apply.

Machine Learning Engineer

Faculty

WHY FACULTY? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen. ABOUT THE TEAM In our Professional and Financial Services Business unit, we bring everything we have learned in more than a decade of Applied AI, and use it to help our clients navigate a rapidly changing landscape. We develop and embed AI solutions which help financial institutions become more efficient, enhance customer experience, and find the commercial upside in uncertain markets. Within the constraints of a highly regulated industry, we see so much opportunity for impactful innovation and are proud to set the gold-standard for marrying technical excellence with safe deployment. ABOUT THE ROLE Join us as a Machine Learning Engineer to deliver bespoke, impactful AI solutions for our diverse Financial Services clients. You will be instrumental in bringing machine learning out of the lab and into the real world, contributing to scalable software architecture and defining best practices. Working with clients, and cross-functional teams, you'll ensure technical feasibility and timely delivery of high-quality, production-grade ML systems. WHAT YOU'LL BE DOING: * Building and deploying production-grade ML software, tools, and infrastructure. * Creating reusable, scalable solutions that accelerate the delivery of ML systems. * Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges. * Leading technical scoping and architectural decisions to ensure project feasibility and impact. * Defining and implementing Faculty’s standards for deploying machine learning at scale. * Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders. WHO WE'RE LOOKING FOR: * You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch. * You possess strong Python skills and solid experience in software engineering best practices. * You bring hands-on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security. * You've worked with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale * You are comfortable with core ML concepts, including probability, statistics, and common learning techniques. * You're an excellent communicator, able to guide technical teams and confidently advise non-technical stakeholders. * You thrive in a fast-paced environment, and enjoy the autonomy to own scope, solve and delivery solutions Our interview process: 1. Talent Team Screen (30 mins) 2. Pair Programming Interview (90 mins) 3. System Design Interview (90 mins) 4. Commercial Interview (60 mins) OUR RECRUITMENT ETHOS We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations. Some of our standout benefits: * Unlimited Annual Leave Policy * Private healthcare and dental * Enhanced parental leave * Family-Friendly Flexibility & Flexible working * Sanctus Coaching * Hybrid Working If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.