Role Overview

Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of:

• Creating custom AI applications that will impact millions of citizens
• Generating high-quality training data for national LLMs
• Upskilling and advisory services to spread the impact of AI

As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners.

At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you.

You will:

• Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies.
• Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment.
• Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability.
• Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks.
• Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again.
• Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials.
• Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases.

Ideally, you have:

• Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector.
• Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI.
• System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core.
• Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools.
• Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them.
• Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy.
• Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it.

Role Overview

Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of:

• Creating custom AI applications that will impact millions of citizens
• Generating high-quality training data for national LLMs
• Upskilling and advisory services to spread the impact of AI

As a Principal AI Ops Architect, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners.

At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you.

You will:

• Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies.
• Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment.
• Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability.
• Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks.
• Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again.
• Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials.
• Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases.

Ideally, you have:

• Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector.
• Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI.
• System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core.
• Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools.
• Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them.
• Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy.
• Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it.

Customer experience

Customer experience at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions.

Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.

The role

We are looking for a Partner Solutions Architect to serve as the technical interface between Nebius and our strategic technology partners, ranging from data platforms and MLOps vendors to AI frameworks and ISVs that build on GPU infrastructure. 

This is a hands-on engineering and integration role. You will design and develop integrated solutions, build reference implementations, enable partner engineering teams, and ensure joint customers succeed with combined offerings. You will influence Nebius’ product roadmap and drive deep technical collaboration across partner ecosystems.

You’re welcome to work from our office in Amsterdam or remotely from any EU country.

Your responsibilities will include: 

• Own the technical relationship with strategic partners as the primary interface to Nebius engineering and product
• Design and architect high-impact integration solutions, delivering clear joint customer value
• Build and maintain reference implementations and production-grade integrations
• Define enterprise-ready integration patterns (networking, security, compliance, observability)
• Translate partner and customer feedback into actionable product and roadmap requirements
• Enable partner teams through technical documentation, training, and demo environments
• Provide technical leadership in joint customer deployments, architecture reviews, and complex troubleshooting

We expect you to have: 

• 5+ years in solutions architecture, partner engineering, or technical pre-sales at cloud or data platform companies
• Strong expertise in cloud infrastructure
• Hands-on experience with GPU-accelerated AI/ML workflows (training, inference, MLOps)
• Proven background in integration architecture (API design, data pipelines, security, observability)
• Experience with Python and IaC tools
• Excellent communication skills with the ability to engage technical and non-technical stakeholders

It will be an added bonus if you have: 

• Track record of building or scaling partner technical programs or ecosystems
• Experience working with or at Snowflake, Databricks, AWS, Azure, or GCP
• Background in ML lifecycle (training pipelines, fine-tuning, inference optimization, RAG

Token Factory is a part of  Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to deploy at massive scale. To deliver on that promise, we need an engineer who can make the platform behave flawlessly under extreme load and recover gracefully when the unexpected happens.

In this role you will own the reliability, performance, and observability of the entire inference stack. Your day starts with designing and refining telemetry pipelines — metrics, logs, and traces that turn hundreds of terabytes of signal into clear, actionable insight. From there you might tune Kubernetes autoscalers to squeeze more efficiency out of GPUs, craft Terraform modules that bake resilience into every new cluster, or harden our request-routing and retry logic so even transient failures go unnoticed by users. When incidents do arise, you’ll rely on the automation and runbooks you helped create to detect, isolate, and remediate problems in minutes, then drive the post-mortem culture that prevents recurrence. All of this effort points toward a single goal: scaling the platform smoothly while hitting aggressive cost and reliability targets.

Success in the role calls for deep fluency with Kubernetes, Prometheus, Grafana, Terraform, and the craft of infrastructure-as-code. You script comfortably in Python or Bash, understand the nuances of alert design and SLOs for high-throughput APIs, and have spent enough time in production to know how distributed back-ends fail in the real world. Experience shepherding GPU-heavy workloads — whether with vLLM, Triton, Ray, or another accelerator stack — will serve you well, as will a background in MLOps or model-hosting platforms. Above all, you care about building self-healing systems, thrive on debugging performance from kernel to application layer, and enjoy collaborating with software engineers to turn reliability into a feature users never have to think about.

If the idea of safeguarding the infrastructure that powers tomorrow’s multimodal AI energizes you, we’d love to hear your story.

Principal Engineer

Location: Waterloo, London, England, UK | Hybrid (1 day per week in office)

Who We Are 

At 8th Light, we bring life to the best ideas.

Founded in 2006 and headquartered in Chicago, we are a technology solutions provider that partners with organizations to solve meaningful challenges and drive sustainable growth. From early-stage startups to global enterprises, we work across industries to optimise our clients’ digital products through product strategy innovation, experiential design, AI solutions, and deep engineering expertise. 

Our commitment to quality means we deliver solutions we’re truly proud of, while our curiosity sparks innovation and breakthrough thinking. 8th Lights thrive in an environment that champions continuous education, fueling our growth through mentorship and hands-on work. We foster an open, collaborative culture grounded in honesty that builds trust, and believe true success is measured by the outcomes we create for our clients.

If this kind of work and our kind of people energizes you, you’ve found the right place. 

Who You Are

You’ve shown long-term repeated success on a variety of projects, typically over the course of 10+ years. You are a trusted expert and leader, often called upon to guide ambiguous initiatives and architect scalable solutions. You bring a blend of deep consulting acumen, technical expertise, and product thinking that drives measurable and impactful outcomes. In your previous experience, you have:

• Demonstrated long-term success on high-stakes consulting engagements across multiple language paradigms, stacks, ecosystems, technical environments, and client industries 
• Built high-quality, maintainable software collaboratively, incrementally, and through an approach tailored towards the unique needs of the clients you’ve served 
• Led the development and delivery of production-grade software using a variety of languages and frameworks, including but not limited to: Python, Java, JavaScript, TypeScript, React, Ruby, Scala, R, SQL, and Go
• Evaluated and strategically applied AI-assistive development tools to accelerate delivery and improve quality
• A track record of understanding, assessing, and embracing new tooling and trends within the software industry
• Experience building or integrating AI/ML-powered features into products or systems (e.g., recommendation engines, NLP models, computer vision, predictive analytics) 
• Used context-appropriate automated testing to inform software design choices and catch bugs
• Successfully led modernization efforts to align legacy systems with short and long-term business needs
• Remedied architecture-level concerns such as scalability, security, reliability, and performance
• Facilitated alignment and collaboration across technical and non-technical stakeholders to move initiatives forward in the face of ambiguity and complexity while balancing technical considerations with product and user needs
• Provided mentorship and team support at scale, while sharing knowledge and improving team practices 
• Actively sought out and effectively given feedback
• Collaboratively led stakeholders to balance technical considerations with product and user needs

What You’ll Do At 8th Light

As a go-to technologist and strategist within 8th Light, you’ll work with a variety of clients, typically one to two in a year, while continuing to deepen your and our collective domain expertise over the course of your career with us. You’ll be responsible for:

• Rapidly building trust with clients, demonstrating technical expertise and understanding of their domain and objectives 
• Guiding technical direction, solving complex problems, and demonstrating best practices while remaining deeply engaged within the codebase
• Working pragmatically to balance technology choices while delivering high-quality work within deadlines
• Advising clients on architecture, scalability and platform evolution, connecting technical decisions to product and business outcomes
• Collaborating on systems that involve the full ML lifecycle from data ingestion and preprocessing, to model deployment, integration, and performance monitoring
• Driving innovation by proactively surfacing new technical approaches and product solutions
• Leading or initiating formal feedback conversations with teams and clients via retrospectives
• Clearly articulating and documenting outcomes and driving forward action items
• Contributing to the health of your team and 8th Light’s culture by modelling our Values
• Designing and managing high-level technical roadmaps for large engagements
• Building your network and maintaining relationships with clients and other industry leaders within your domain
• Coaching client engineering teams, transferring knowledge and leveling up practices
• Influencing client CTOs and executive decisions. Planning and execute technical work that involves stakeholders outside of project boundaries such as across a client's technical organization
• Participating in account planning; opportunity identification.
• Facilitating retrospectives, strategy sessions, and technical deep-dives to improve team and project outcomes
• Identifying, mitigating, and resolving blockers to team progress
• Contributing to 8th Light by serving as a mentor, leading or designing workshops internally or for clients, representing 8th Light in the tech community, or supporting our hiring processes
• Demonstrating leadership in scalable system design, modular architecture, and platform- or product-oriented development.
• Bringing depth in testing strategies, observability, fault tolerance, and secure engineering practices.
• Applying architectural patterns to evaluate tradeoffs and drive clear, documented design rationale.

Strongly Preferred Skills

We work across many areas, and encourage anyone with the experience listed above to apply. We would particularly like to encourage applicants with experience in the following areas:

• Delivering and advising on enterprise-grade AI systems, including RAG pipelines, vector search, and agentic frameworks (e.g., LangChain, LlamaIndex, Crew AI, AutoGen, n8n), ensuring scalable, production-ready solutions that empower developers and align with business outcomes.
• DevSecOps & DevOps
• MLOps
• Infrastructure as Code
• Data Engineering: including platforms like Databricks for data processing and analytics.

Building a truly diverse, equitable, and inclusive workplace is an ongoing journey, and we’re excited to keep learning and growing together. We have a proud tradition of hiring talented colleagues with real-world career experiences. 

How You’ll be Supported

At 8th Light, we believe our people are our greatest asset. Their growth, well-being, and success shape our future. 

• Our wellness package is designed with the Whole YOU in mind and includes:
• A robust L&D programme featuring unlimited access to thousands of books, courses, and expert-led training on the O'Reilly learning platform.
• Annual financial stipend and time allotment for learning & development
• Coworking support for our global team
• 12 weeks of new parent leave available for eligible employees

See our full list of Benefits. 

A Note on Compensation

At 8th Light, we are committed to a compensation philosophy that is transparent, fair, and helps us attract and retain top talent in alignment with our company’s strategic growth goals and clients’ needs.

We benchmark our salaries using Geographic Structures to establish competitive pay ranges within the regions where 8th Lights live. Our pay ranges for our Principal Engineer position within London is: £92-818-£116-122 GBP

Reach out to recruiting@8thlight.com for more relevant information pertaining to your local market.

8th Light Hubs and Geographies

8th Light's culture is rooted in strong connections that extend across our teams, regions, and beyond client work. We are a distributed team across the United States, Canada, and the United Kingdom, with hubs in Chicago, London, Los Angeles, New York, and Seattle. 

• London Co-working: Employees working from our London hub follow a hybrid model, which includes a minimum of one day per week in our Waterloo Office. This co-working day is designed to encourage collaboration and further strengthen our community.In most cases, our consulting engagements do not require travel.

We hope to see you apply! 

^#LI-Hybrid

Who we are

The Role 

Much of our work takes place in high-security on-premise environments, and we are looking for Site Reliability Engineer to support our high security environments.

Your role as a Site Reliability Engineer will be to design, implement, and manage our on-premise Kubernetes infrastructure.

We are looking for engineers with a strong work ethic and prioritisation skills. We value team players who communicate clearly, share knowledge generously, and collaborate effectively to move their team — and our mission—forward. 

The day-to-day

• As a SRE, you will design and build cloud-native infrastructure platforms on-premises, focusing on Kubernetes-based solutions that enable our development teams to operate services at scale.

• You will create robust observability frameworks using Grafana, Prometheus, and distributed tracing to ensure system reliability and performance

• You will architect and implement secure, multi-tenant Kubernetes clusters with strong access controls, policy-as-code governance, and zero-trust networking between red and black network domains. You will develop operators and controllers to automate infrastructure provisioning and compliance

• You will build and maintain MLOps platforms enabling AI researchers to deploy, monitor, and scale machine learning models in production.

• You will collaborate closely with our Security teams to implement supply chain security, container scanning, and runtime protection across our cloud-native stack

Key Skills 

• Scripting: experience in either Python, Go, Rust or Bash/ Shell for automation and tooling  

• Experience with GitOps workflows and CI/CD automation

• Kubernetes Expertise: deep experience operating production Kubernetes clusters, writing custom controllers/operators, and implementing service mesh architectures (Istio/Linkerd)

• Cloud-Native Technologies: hands-on experience with CNCF ecosystem, e.g. including Helm, ArgoCD, Flux and container runtime security tools like Falco

• Observability Stack: expert-level knowledge of Grafana, Prometheus, Loki, Tempo, and OpenTelemetry. Experience building custom dashboards, alerts, and SLI/SLO frameworks

• Networking: Expert understanding of networking concepts, protocols and security

• MLOps Platforms: experience with Kubeflow, MLflow, or similar platforms

• Infrastructure as Code: proficiency with Terraform, Ansible, and Kubernetes manifest templating. Experience with policy-as-code tools like OPA/Gatekeeper

• System Administration: deep understanding of Linux/Unix system administration and highly available, distributed systems

• Comfortable building out data and telemetry pipelines for debugging and future-proofing solutions

You should apply if you

• Have a high level of personal integrity, reliability, and attention to detail

• Have a software engineering mindset with a passion for building platforms and tools that multiply developer productivity

• Have experience running cloud-native workloads in on-premises or air-gapped environments

• Are willing to relocate to Munich, London, or Berlin.

Note: We operate at an intersection where women, as well as other minority groups, are systemically under-represented. We encourage you to apply even if you don’t meet all the listed qualifications;  ability and impact cannot be summarised in a few bullet points.

Join Helsing and work with world-leading experts in their fields 

• Helsing’s work is important. You’ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns. 

• The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world. 

• Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defence industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward. 

• In our domain, success is a matter of order-of-magnitude improvements and novel capabilities. This means we take bets, aim high, and focus on big opportunities. Despite being a relatively young company, Helsing has already been selected for multiple significant government contracts.  

• We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it. Teams and individual engineers are trusted (and encouraged) to practise responsible autonomy and critical thinking, and to focus on outcomes, not conformity. At Helsing you will have a say in how we (and you!) work, the opportunity to engage on what does and doesn’t work, and to take ownership of aspects of our culture that you care deeply about. 

What we offer

• A focus on outcomes, not time-tracking

• Competitive compensation and VSOP options

• Relocation support

• Social and education allowances

• Regular company events and all-hands to bring together employees as one team across Europe

• A hands-on onboarding program (affectionately labelled “Infraduction”), in which you will be building tooling and applications to be used across the company. This is your opportunity to learn our tech stack, explore the company, and learn how we get things done - all whilst working with other engineering teams from day one 

Helsing is an equal opportunities employer. We are committed to equal employment opportunity regardless of race, religion, sexual orientation, age, marital status, disability or gender identity. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation.

About Graphcore

At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.  

Job Summary

As a Senior Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Working closely with the Software development and Research teams, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation at scale, eager to make a tangible impact in this rapidly evolving field.

The Team

The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. We build reference applications, contribute to key software libraries e.g. optimising kernels for efficiency on our hardware, and collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications.

If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you!

Responsibilities and Duties

• Implement latest machine learning models and optimise them for performance and accuracy, scaling to 1000s of accelerators.
• Test and evaluate new internal software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews.
• Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency.
• Design and conduct experiments on novel AI methods, implement them and evaluate results.
• Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware.
• Engage with AI community and keep in touch with the latest developments in AI.

Candidate Profile

Essential:

• Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field.
• Proficiency in deep learning frameworks like PyTorch/JAX.
• Strong Python or C++ software development skills
• Expertise in deep learning from model training to optimisation and evaluation.
• Experience in distributed training or inference of ML models across 64+ accelerators.
• Capable of designing, executing and reporting from ML experiments.
• Developed deep understanding of performance bottlenecks and how to overcome them.
• Ability to move quickly in a dynamic environment
• Enjoy cross-functional work collaborating with other teams.
• Strong communicator - able to explain complex technical concepts to different audiences.

Desirable:

• Experience in one or more of:
  • MLOps for Kubernetes-based clusters
  • Building production systems with large language models
  • Efficient computing based on low-precision arithmetic.
• Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models.
• Familiarity with HPC systems and networking including Infiniband, NVLink, RoCE technologies.
• Have contributed to open-source projects or published research papers in relevant fields.
• Knowledge of cloud computing platforms.
• Keen to present, publish and deliver talks in the AI community.

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

About Graphcore

At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary

As a Senior Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Working closely with the Software development and Research teams, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation at scale, eager to make a tangible impact in this rapidly evolving field.

The Team

The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. We build reference applications, contribute to key software libraries e.g. optimising kernels for efficiency on our hardware, and collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications.

If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you!

Responsibilities and Duties

• Implement latest machine learning models and optimise them for performance and accuracy, scaling to 1000s of accelerators.
• Test and evaluate new internal software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews.
• Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency.
• Design and conduct experiments on novel AI methods, implement them and evaluate results.
• Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware.
• Engage with AI community and keep in touch with the latest developments in AI.

Candidate Profile

Essential:

• Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field.
• Proficiency in deep learning frameworks like PyTorch/JAX.
• Strong Python or C++ software development skills
• Expertise in deep learning from model training to optimisation and evaluation.
• Experience in distributed training or inference of ML models across 64+ accelerators.
• Capable of designing, executing and reporting from ML experiments.
• Developed deep understanding of performance bottlenecks and how to overcome them.
• Ability to move quickly in a dynamic environment
• Enjoy cross-functional work collaborating with other teams.
• Strong communicator - able to explain complex technical concepts to different audiences.

Desirable:

• Experience in one or more of:
  • MLOps for Kubernetes-based clusters
  • Building production systems with large language models
  • Efficient computing based on low-precision arithmetic.
• Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models.
• Familiarity with HPC systems and networking including Infiniband, NVLink, RoCE technologies.
• Have contributed to open-source projects or published research papers in relevant fields.
• Knowledge of cloud computing platforms.
• Keen to present, publish and deliver talks in the AI community.

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

Senior: PLN 260,400 - 352,200
Staff: PLN 350,700 - 474,400
Subject to alignment to the responsibilities and duties of the role - we currently have multiple positions available at both Senior and Staff level

About Graphcore 

At Graphcore, we’re building the future of AI compute.

We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.

As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.

To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.

We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence

Job Summary

As a Senior Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Working closely with the Software development and Research teams, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation at scale, eager to make a tangible impact in this rapidly evolving field.

The Team

The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. We build reference applications, contribute to key software libraries e.g. optimising kernels for efficiency on our hardware, and collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications.

If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you!

Responsibilities and Duties

• Implement latest machine learning models and optimise them for performance and accuracy, scaling to 1000s of accelerators.
• Test and evaluate new internal software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews.
• Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency.
• Design and conduct experiments on novel AI methods, implement them and evaluate results.
• Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware.
• Engage with AI community and keep in touch with the latest developments in AI.

Candidate Profile

Essential:

• Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field.
• Proficiency in deep learning frameworks like PyTorch/JAX.
• Strong Python or C++ software development skills
• Expertise in deep learning from model training to optimisation and evaluation.
• Experience in distributed training or inference of ML models across 64+ accelerators.
• Capable of designing, executing and reporting from ML experiments.
• Developed deep understanding of performance bottlenecks and how to overcome them.
• Ability to move quickly in a dynamic environment
• Enjoy cross-functional work collaborating with other teams.
• Strong communicator - able to explain complex technical concepts to different audiences.

Desirable:

• Experience in one or more of:
  • MLOps for Kubernetes-based clusters
  • Building production systems with large language models
  • Efficient computing based on low-precision arithmetic.
• Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models.
• Familiarity with HPC systems and networking including Infiniband, NVLink, RoCE technologies.
• Have contributed to open-source projects or published research papers in relevant fields.
• Knowledge of cloud computing platforms.
• Keen to present, publish and deliver talks in the AI community.

Benefits

In addition to a competitive salary, Graphcore offers annual leave policy, medical and dental health plans, a gym card, and employee pension (matched up to 4%). We review our benefits on a yearly basis to ensure we offer a valuable and rewarding benefits programme to our employees. 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.

About Graphcore

At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary

As a Senior Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Working closely with the Software development and Research teams, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation at scale, eager to make a tangible impact in this rapidly evolving field.

The Team

The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. We build reference applications, contribute to key software libraries e.g. optimising kernels for efficiency on our hardware, and collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications.

If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you!

Responsibilities and Duties

• Implement latest machine learning models and optimise them for performance and accuracy, scaling to 1000s of accelerators.
• Test and evaluate new internal software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews.
• Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency.
• Design and conduct experiments on novel AI methods, implement them and evaluate results.
• Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware.
• Engage with AI community and keep in touch with the latest developments in AI.

Candidate Profile

Essential:

• Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field.
• Proficiency in deep learning frameworks like PyTorch/JAX.
• Strong Python or C++ software development skills
• Expertise in deep learning from model training to optimisation and evaluation.
• Experience in distributed training or inference of ML models across 64+ accelerators.
• Capable of designing, executing and reporting from ML experiments.
• Developed deep understanding of performance bottlenecks and how to overcome them.
• Ability to move quickly in a dynamic environment
• Enjoy cross-functional work collaborating with other teams.
• Strong communicator - able to explain complex technical concepts to different audiences.

Desirable:

• Experience in one or more of:
  • MLOps for Kubernetes-based clusters
  • Building production systems with large language models
  • Efficient computing based on low-precision arithmetic.
• Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models.
• Familiarity with HPC systems and networking including Infiniband, NVLink, RoCE technologies.
• Have contributed to open-source projects or published research papers in relevant fields.
• Knowledge of cloud computing platforms.
• Keen to present, publish and deliver talks in the AI community.

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

The role

As a Cloud Site Reliability Engineer at Wayve, you will build and scale the reliability foundations of our AI cloud platform. This includes our Model Development Platform (powering end-to-end model development from raw data to on-road experimentation) and our GPU Compute platform (large-scale, multi-tenant GPU fleets and scheduling systems driving model training and inference at scale).

This is a founding Cloud SRE role. You won’t inherit a mature SRE function, you’ll help create it. You will define the frameworks, automation, and operational standards that ensure our model development infrastructure, distributed systems, and large compute clusters operate predictably, efficiently, and at scale.

This role sits at the intersection of AI research, large-scale cloud infrastructure, and production operations. Your work will directly enable faster model training, reliable experimentation, and scalable AI deployment by ensuring our cloud infrastructure is resilient and performant.

Key responsibilities

Reliability & Platform Ownership

• Own the reliability, availability, and performance of the Model Dev Platform and GPU Compute environments.
• Define and operationalise SLOs, SLIs, and error budgets across platform services.
• Improve capacity planning, scaling strategies, and resource efficiency across large GPU-backed clusters.
• Partner with ML, platform, and software teams to establish clear production readiness standards.
  
  

Incident Response & On-Call

• Participate in a 24/7 on-call rotation as first-line response for cloud and cluster-related incidents.
• Lead incident triage, escalation, communications, and root cause analysis.
• Translate post-incident learning into durable architectural or automation improvements.
• Continuously reduce alert noise and recurring operational burden.
  
  

Observability & Operational Excellence

• Design and operate monitoring, logging, tracing, and alerting systems that enable rapid detection and recovery.
• Build dashboards that reflect real user-centric platform health (not just infrastructure metrics).
  Improve deployment safety through better change management, validation, and rollback mechanisms.
  
  

Automation & Tooling

• Build automation for cluster operations, training workflows, remediation, and scaling tasks.
• Implement self-healing patterns and resilient recovery workflows.
• Harden CI/CD and release processes to improve deployment safety and velocity.
• Support infrastructure-as-code and policy-driven guardrails to ensure secure, reliable cloud environments.

About you

In order to set you up for success as a Cloud Site Reliability Engineer at Wayve, we’re looking for the following skills and experience.

Essential skills

• Proven experience in an SRE, Production Engineer, or Cloud Reliability role supporting large-scale cloud systems.
• Strong Kubernetes experience, including operating production clusters.
• Hands-on experience running production workloads in AWS, GCP, or Azure.
• Experience operating complex distributed systems in production, ideally including compute-heavy or high-performance workloads.
• Experience working with large compute clusters; exposure to AI/ML training or inference workloads strongly preferred.
• Strong Linux fundamentals and proficiency in at least one scripting or systems language (e.g. Python, Go, C++) with a bias toward automation.
• Deep troubleshooting skills across networking, storage, distributed systems, and performance at scale.
• Experience designing and operating observability stacks (e.g. Datadog, Prometheus, Grafana, OpenTelemetry).
• Clear communication skills, including leading incidents, writing postmortems, and influencing teams to prioritise reliability improvements.

Desirable skills

• Experience operating GPU-backed environments or large-scale ML infrastructure.
• Experience running model training or inference pipelines in production (MLOps).
• Familiarity with infrastructure-as-code (e.g. Terraform) and secure cloud production environments.
• Experience defining and running SLOs/SLIs and building reliability programs across multiple teams.
• Experience as an early or founding SRE hire establishing processes from scratch.
• Interest in helping shape and grow a Cloud SRE function, with potential to take on leadership responsibilities over time.

This is a full-time role based in our office in London (2 days a week in the office).  At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.

The role

This is a rare opportunity to be a founding Staff SRE shaping the reliability of large-scale AI systems and GPU compute infrastructure from the ground up.

As a Staff Cloud Site Reliability Engineer at Wayve, you will build and scale the reliability foundations of our AI cloud platform. This includes our Model Development Platform (powering end-to-end model development from raw data to on-road experimentation) and our GPU Compute platform (large-scale, multi-tenant GPU fleets and scheduling systems driving model training and inference at scale).

This is a founding Cloud SRE role. You won’t inherit a mature SRE function, you’ll help create it. You will define the frameworks, automation, and operational standards that ensure our model development infrastructure, distributed systems, and large compute clusters operate predictably, efficiently, and at scale.

This role sits at the intersection of AI research, large-scale cloud infrastructure, and production operations. Your work will directly enable faster model training, reliable experimentation, and scalable AI deployment by ensuring our cloud infrastructure is resilient and performant.

Key responsibilities

Reliability & Platform Ownership

• Own the reliability, availability, and performance of the Model Dev Platform and GPU Compute environments.
• Define and operationalise SLOs, SLIs, and error budgets across platform services.
• Improve capacity planning, scaling strategies, and resource efficiency across large GPU-backed clusters.
• Partner with ML, platform, and software teams to establish clear production readiness standards.
  
  

Incident Response & On-Call

• Participate in a 24/7 on-call rotation as first-line response for cloud and cluster-related incidents.
• Lead incident triage, escalation, communications, and root cause analysis.
• Translate post-incident learning into durable architectural or automation improvements.
• Continuously reduce alert noise and recurring operational burden.
  
  

Observability & Operational Excellence

• Design and operate monitoring, logging, tracing, and alerting systems that enable rapid detection and recovery.
• Build dashboards that reflect real user-centric platform health (not just infrastructure metrics).
  Improve deployment safety through better change management, validation, and rollback mechanisms.
  
  

Automation & Tooling

• Build automation for cluster operations, training workflows, remediation, and scaling tasks.
• Implement self-healing patterns and resilient recovery workflows.
• Harden CI/CD and release processes to improve deployment safety and velocity.
• Support infrastructure-as-code and policy-driven guardrails to ensure secure, reliable cloud environments.

About you

In order to set you up for success as a Cloud Site Reliability Engineer at Wayve, we’re looking for the following skills and experience.

Essential skills

• Proven experience in an SRE, Production Engineer, or Cloud Reliability role supporting large-scale cloud systems.
• Experience operating GPU-backed environments or large-scale ML infrastructure.
• Experience running model training or inference pipelines in production (MLOps).
• Strong Kubernetes experience, including operating production clusters.
• Hands-on experience running production workloads in AWS, GCP, or Azure.
• Experience operating complex distributed systems in production, ideally including compute-heavy or high-performance workloads.
• Experience working with large compute clusters; exposure to AI/ML training or inference workloads strongly preferred.
• Strong Linux fundamentals and proficiency in at least one scripting or systems language (e.g. Python, Go, C++) with a bias toward automation.
• Deep troubleshooting skills across networking, storage, distributed systems, and performance at scale.
• Experience designing and operating observability stacks (e.g. Datadog, Prometheus, Grafana, OpenTelemetry).
• Clear communication skills, including leading incidents, writing postmortems, and influencing teams to prioritise reliability improvements.

Desirable skills

• Familiarity with infrastructure-as-code (e.g. Terraform) and secure cloud production environments.
• Experience defining and running SLOs/SLIs and building reliability programs across multiple teams.
• Experience as an early or founding SRE hire establishing processes from scratch.
• Interest in helping shape and grow a Cloud SRE function, with potential to take on leadership responsibilities over time.

This is a full-time role based in our office in London (2 days a week in the office).  At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.

What You’ll Do:

The Monolith AI Platform Engineering Team at CoreWeave is responsible for building and scaling the data and workflow backbone that powers the world’s most advanced engineering simulation and AI workflows — our ambition is to become the super‑intelligent AI test lab for the engineering industry, helping customers ship science, faster. From high‑throughput data ingestion and feature pipelines to model training and real‑time inference, our platform delivers the performant, reliable, and trustworthy data foundation trusted by the world’s largest engineering companies.

The Staff Data Engineer will own and evolve Monolith’s platform data services and ETL offerings — the data onboarding, preparation, and lineage capabilities that turn fragmented, real‑world engineering data into production‑ready training and inference pipelines. You’ll partner with Product, Engineering, and Customer‑facing teams to deeply understand client data challenges and translate them into scalable, self‑serve data platform features.

About the Role:

We’re seeking a Staff Data Engineer who can own Monolith’s data platform surface end‑to‑end: from offline batch pipelines and large historical backfills to low‑latency, real‑time streaming data flows that power online inference and feedback loops. You’ll define and drive our data architecture, champion data quality and lineage, and decide how customer data moves through Monolith from raw ingestion to governed, observable, and reproducible training sets.

You’ll primarily work with internal teams (Product, Customer Success, Forward‑Deployed Engineers, Software Engineers, Data Scientists), and step in as a domain expert when clients need deeper guidance.

In this role, you will:

• Own Monolith’s Data Platform & ETL Surface
• Lead the architecture and evolution of core data services for ingestion, transformation, validation, and lineage across training and inference workloads.
• Design and maintain end‑to‑end data models and schemas that make complex engineering, simulation, and telemetry data discoverable, reusable, and performant.
• Define standards, contracts, and APIs for how product teams and integrations interact with data services.
• Design & Operate Batch + Streaming Pipelines
• Build and operate batch pipelines for large‑scale historical imports, retraining data sets, and migrations from legacy environments.
• Design and implement streaming pipelines (e.g., using Kafka or similar technologies) for event‑driven or real‑time ingestion and transformation that support online inference, monitoring, and feedback loops.
• Select and integrate off‑the‑shelf, industry‑proven ETL / ELT technologies (e.g., workflow orchestrators, ingestion frameworks, transformation engines) and own their rollout and long‑term operation.
• Champion Data Lineage, Governance & DataOps
• Implement and maintain end‑to‑end data lineage from source systems to derived features and model artifacts, enabling reproducibility, compliance, and faster debugging.
• Establish DataOps practices: CI/CD for pipelines, observability (metrics, logs, traces), and operational runbooks for data incidents.
• Help define data quality and governance standards in partnership with Security, Compliance, and Customer Success, including support for privacy and regulatory needs (e.g., GDPR‑aligned flows and data residency discussions).
• Partner Across Monolith & CoreWeave
• Work with Monolith product and engineering teams (platform, agents, experiments, reliability) to expose data services that unlock new user workflows and AI capabilities.
• Collaborate with CoreWeave infrastructure and AI platform teams to leverage storage, compute, and observability for reliable data flows.
• Serve as a technical escalation point for forward‑deployed and customer‑facing engineers when questions go deeper than their playbooks (e.g., architecture diagrams of data flow, lineage, and governance constraints).

Who You Are:

• Experience & Level
• Typically 8+ years of experience as a Data Engineer / Data Platform Engineer (or similar), including ownership of production data pipelines and architectural decisions.
• Demonstrated Staff‑level impact: leading critical data domains and cross‑team initiatives.
• Data Engineering & Architecture
• Deep experience designing end‑to‑end data architectures that cover ingestion, storage, transformation, serving, and observability.
• Strong, hands‑on experience with both batch and streaming pipelines:
• Batch: scheduled workloads, historical backfills, retraining pipelines.
• Streaming: Kafka or similar event streaming platforms plus real‑time transformation patterns for low‑latency consumption.
• Proficiency with SQL and at least one major analytical database or data warehouse (e.g., PostgreSQL or similar) including schema design and performance tuning
• Proficiency with Spark, Ray or similar distributed data processing frameworks.
• Solid understanding of data modeling (event logs, star schemas, feature tables) in multi‑tenant SaaS or platform contexts.
• Tooling & Ecosystem
• Hands‑on with data orchestration and ETL tooling (e.g., Airflow, dbt, Dagster, Temporal, or equivalents) and able to evaluate and recommend tools that fit our needs.
• Experience integrating and operating off‑the‑shelf data infrastructure (not just bespoke systems), including rollout, migration plans, and ongoing ownership.
• Familiarity with cloud infrastructure and containerization (Docker, Kubernetes, at least one major cloud provider) for deploying and scaling data workloads.
• Data Lineage, Quality & DataOps
• Extensive experience implementing data lineage solutions and using them for debugging, compliance, and auditability.
• Strong background in data quality: validation frameworks, monitoring, and guardrails that prevent bad data from reaching downstream consumers.
• Proficiency with DevOps / DataOps practices: infra‑as‑code, CI/CD for pipelines, runbooks, and participation in on‑call / incident response for data issues.
• Programming, Systems & Communication
• Strong programming skills in Python for building data services, transformations, and platform integrations, with an emphasis on maintainability and tests.
• Comfortable working in service‑oriented architectures, reasoning about data contracts, SLAs, and failure modes across services.
• Clear written and verbal communicator who can:
• Explain data architectures and trade‑offs to internal stakeholders, and
• Occasionally join client conversations as a deep domain expert to answer questions about data flows, security, and governance (e.g., with CIOs, heads of data, or security counterparts), while day‑to‑day client interaction is handled by forward‑deployed teams.

Preferred:

• Experience in ML/AI platforms or MLOps environments where data pipelines feed experimentation, training, and inference workflows at scale.
• Background with time‑series, simulation, or experimental data (e.g., physical test benches, sensors, engineering simulations).
• Familiarity with feature stores, experiment tracking systems, or model registries and their integration with upstream pipelines.
• Experience designing data systems for regulated or safety‑critical domains, including privacy, residency, and retention considerations.

Wondering if you’re a good fit?

We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams — even if you aren’t a 100% skill or experience match. If some of this describes you, we’d love to talk:

• Product‑minded – you design data platforms and pipelines that are intuitive to use and unlock real workflows for engineers and customers.
• Systems thinker – you enjoy mapping complex data flows, understanding failure modes, and building robust, observable systems.
• Pragmatic – you balance solid engineering with shipping value quickly, knowing when to invest in abstractions and when to deliver incremental improvements.
• Collaborative owner – you partner well across engineering, product, and customer‑facing teams, and you feel responsible for outcomes, not just code.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper‑growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best‑in‑Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking, and foster an environment that encourages collaboration and innovative solutions to complex problems. As we get set for takeoff, the organization’s growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

What You’ll Do:

The Monolith AI Platform Engineering Team at CoreWeave is responsible for building and scaling the data and workflow backbone that powers the world’s most advanced engineering simulation and AI workflows — our ambition is to become the super‑intelligent AI test lab for the engineering industry, helping customers ship science, faster. From high‑throughput data ingestion and feature pipelines to model training and real‑time inference, our platform delivers the performant, reliable, and trustworthy data foundation trusted by the world’s largest engineering companies.

The Senior DataOps Engineer II will own and drive all things data observability and operations across our client estate — building the practices, tooling, and culture that make Monolith’s data flows debuggable, auditable, and safe to evolve. You’ll sit at the intersection of platform engineering, data engineering, and reliability, implementing end‑to‑end lineage and DataOps practices while mentoring data producers and consumers on how to manage data as a first‑class product.

You’ll partner closely with Monolith’s Product, Engineering and forward‑deployed teams, as well as with CoreWeave’s infrastructure and AI platform groups, to turn fragmented, real‑world engineering data into well‑governed, observable, and operationally robust pipelines powering our SaaS platform and client‑specific deployments.

About the Role:

We’re seeking an Senior DataOps Engineer II who can act as the hands‑on owner for Monolith’s data observability and operational surface: from batch and streaming pipelines running on our platform, through to the lineage, quality, and runbooks that keep customer environments healthy.

You’ll define and roll out DataOps practices (CI/CD, infra‑as‑code, data SLOs, incident response) across the Monolith estate, implement end‑to‑end data lineage and observability, and serve as the go‑to mentor for engineering teams and client‑facing colleagues on best‑practice data management.

In this role, you will:

• Own Monolith’s Data Observability & Operations Surface
• Design and implement the end‑to‑end observability stack for data workloads (metrics, logs, traces, and data‑quality signals) across batch and streaming pipelines.
• Define and maintain operational SLOs/SLAs for critical data flows powering training, inference, and analytics, and ensure they are measurable and actionable.
• Build dashboards, alerts, and runbooks that allow engineers and on‑call responders to quickly detect, triage, and remediate data incidents.
• Standardise “golden paths” for how teams instrument pipelines, expose health signals, and respond to data‑related failures.

• Implement Data Lineage, Quality & Governance
• Deploy and maintain end‑to‑end data lineage for key domains — from client sources through transformations to features, models, and downstream analytics  so teams can debug, audit, and reason about change.
• Define and roll out data quality checks (schema, freshness, completeness, distribution, drift) and ensure failures integrate cleanly into alerting and incident workflows.
• Partner with Security, Compliance, and customer‑facing teams to encode data governance requirements (e.g., retention, residency, access controls) into our pipelines and tooling.
• Help shape metadata models and catalog conventions so that producers and consumers can reliably discover, understand, and use shared datasets.

• Enable DataOps Practices Across Teams
• Establish CI/CD patterns for data pipelines and related infrastructure, including testing strategies, promotion workflows, and change‑management guardrails.
• Drive adoption of infra‑as‑code for data infrastructure (e.g., pipeline orchestration, storage, observability components), reducing manual drift across environments.
• Define and continuously improve DataOps processes — incident response, post‑incident review, change review, on‑call rotations — with a focus on learning rather than blame.
• Evaluate and integrate best‑of‑breed DataOps and observability tooling where it accelerates our teams, balancing build vs. buy pragmatically.

• Partner Across Monolith, CoreWeave & Clients
• Work with Monolith platform, data, agent, and reliability teams to expose observability and lineage as shared services and patterns other engineers can build on.
• Collaborate with CoreWeave infrastructure and AI platform teams to leverage underlying storage, compute, networking, and observability in service of robust data flows.
• Serve as a technical escalation point for forward‑deployed and customer‑facing engineers when data issues cross service boundaries or require deeper architectural insight.
• Mentor data producers (product teams, integrations, forward‑deployed engineers) and data consumers (data scientists, analysts, client engineers) on resilient schemas, contracts, and operational practices.

Who You Are:

• Experience & Level
• Typically 5–6+ years of experience in DataOps, Data Engineering, DevOps/SRE for data platforms, or similar roles, including end‑to‑end ownership of production data pipelines and their operations.
• Proven track record of operating at Senior IC scope: leading cross‑team initiatives, introducing new practices/tooling, and improving reliability at the platform level.

• DataOps, Pipelines & Tooling
• Strong hands‑on experience designing, deploying, and operating data pipelines in production (batch and/or streaming), including failure modes, retries, and backfills.
• Practical experience with data orchestration and ETL/ELT tooling (e.g., Airflow, Dagster, dbt, Temporal, or similar) and comfort evaluating and integrating new tools where appropriate.
• Solid SQL and/or Spark skills and experience with at least one major analytical database or warehouse; familiarity with time‑series / telemetry data is a plus.

• Observability, Lineage & Data Quality
• Extensive experience implementing data observability — metrics, logging, tracing, dashboards, and alerting — for data‑centric workloads.
• Hands‑on work with data quality frameworks and/or observability platforms to monitor freshness, completeness, schema changes, and anomalies.
• Experience deploying and using data lineage or metadata/catalog solutions, and applying them to debugging, compliance, and change‑impact analysis.

• Platform, Infrastructure & Automation
• Comfortable working in containerised, cloud‑native environments (Kubernetes plus at least one major cloud provider); experience with GPU‑ or compute‑intensive workloads is a bonus.
• Strong automation mindset: infra‑as‑code, CI/CD, and configuration management for data infrastructure and observability components.
• Proficient in Python for building tooling, pipeline glue, and platform integrations; additional languages are a plus.

• Collaboration, Mentorship & Communication
• Clear communicator who can explain complex data flows and failure modes to both deeply technical and non‑specialist audiences.
• Experience mentoring engineers and data practitioners on better data management, observability, and operational hygiene — through documentation, examples, reviews, and office hours.
• Comfortable working in a fast‑moving, high‑ambiguity environment where we balance rapid iteration with the safety and reliability demanded by enterprise engineering clients.

Preferred:

• Experience in ML/AI platforms or MLOps environments where data pipelines power experimentation, training, and inference at scale.
• Background with test, simulation, or time‑series data (e.g., physical test benches, battery labs, automotive/aerospace R&D).
• Familiarity with feature stores, experiment tracking, or model registries and their interaction with upstream data pipelines.
• Prior work in multi‑tenant SaaS platforms, especially those with strong compliance, observability, and uptime requirements.
• Experience supporting or partnering closely with forward‑deployed / professional services teams in complex customer environments.

Wondering if you’re a good fit?

We believe in investing in our people, and value candidates who bring diverse experiences — even if you don’t tick every single box. Here are a few qualities we’ve found compatible with our team. If some of this sounds like you, we’d love to talk:

• Data‑obsessed operator – You care deeply about making data systems observable, predictable, and easy to reason about, not just “working most of the time.”
• Systems thinker – You enjoy mapping complex data flows across services, understanding failure modes, and designing for graceful degradation and rapid recovery.
• Pragmatic – You know when to build the ideal abstraction and when to ship the smallest change that meaningfully reduces risk or toil.
• Collaborative mentor – You get energy from helping other teams level up their data practices, and you can influence without heavy process or authority.
• Owner’s mindset – You feel responsible for the outcomes of the platform as a whole, not just the code you write, and you follow issues across boundaries until they’re truly resolved.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper‑growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best‑in‑Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking, and foster an environment that encourages collaboration and innovative solutions to complex problems. As we get set for takeoff, the organization’s growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

What You’ll Do:

The Data Science team is focused on developing an advanced reliability platform. This system covers various aspects of data processing and analysis, including data intake, deriving meaningful metrics, identifying unusual patterns, predicting potential issues, finding slow processes in distributed systems, and using automated analysis to determine causes. We collaborate closely with internal teams like Fleet, Infrastructure, and AI Platform to enhance system stability, optimize resource use, shorten resolution times, and maintain service availability and financial performance.

About the role:

As a Senior Data & MLOps Engineer, you will design and scale the infrastructure supporting the GPU Intelligence Platform. This involves building pipelines for handling data, features, model training, and delivering insights and predictions for system health and optimization. You will transition the system from initial prototypes to a production environment operating across the fleet, focusing on scalability, separating real-time service from periodic processing, and dynamic resource management based on system load and data frequency. You will architect and deploy these scalable distributed services using orchestration technologies.

Key responsibilities:

• Design and implement scalable data ingestion pipelines.
• Build feature processing and baseline computation systems.
• Productionize models for prediction and detection.
• Develop and operate low-latency service and robust offline workflows.
• Architect horizontally scalable services with clear separation between components, leveraging orchestration for distribution.
• Implement monitoring and feedback loops for continuous model and signal improvement.
• Collaborate with Platform teams to integrate operational signals into monitoring and diagnostics.
• Implement a scalable solution for mitigation and structured analysis.

Who You Are:

• 7+ years of experience in data engineering, distributed systems, MLOps, or infrastructure ML roles in production environments.
• Proven experience building high-throughput streaming or telemetry pipelines (e.g., Kafka, Pulsar, Kinesis, or equivalent).
• Strong experience designing time-series feature pipelines and operating large-scale observability systems.
• Experience building and maintaining feature stores and ensuring offline/online feature parity.
• Hands-on experience deploying ML models to production, including versioning, monitoring, rollback, and drift detection.
• Experience designing scalable microservices deployed in Kubernetes-based environments.
• Strong proficiency in Python and at least one systems language (Go, Rust, or C++).
• Experience working with distributed compute or training systems (e.g., NCCL, PyTorch Distributed, Spark, Ray, Slurm).
• Familiarity with GPU telemetry systems such as NVML or DCGM and hardware-level monitoring concepts.
• Demonstrated experience scaling systems from Proof-of-Concept to production-grade, fleet-level deployments.

Preferred: 

• Experience working on GPU fleet management, hyperscale infrastructure, or AI training clusters.
• Experience building anomaly detection or failure prediction systems for hardware or distributed systems.
• Experience implementing distributed straggler detection or collective-level performance analysis systems.
• Experience developing agentic or LLM-powered reasoning systems for diagnostics or operational intelligence.
• Background in reliability engineering or SRE practices.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk. 

• You love building systems that turn raw infrastructure telemetry into actionable intelligence.
• You’re curious about distributed systems failure modes, GPU performance pathologies, and reliability engineering at scale.
• You’re excited by the idea of moving from anomaly detection to prediction to autonomous root cause reasoning.
• You enjoy designing platforms that protect uptime, revenue, and customer trust through proactive systems thinking.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! 

What You’ll Do:

The Monolith AI Engineering Team at CoreWeave is responsible for building and scaling the core platform that powers the world’s most advanced engineering simulation and AI workflows. From evolving distributed architecture to enabling the next generation of agentic applications and physical AI, this team delivers the performant, reliable, and scalable foundation trusted by the world’s largest engineering companies.

About the role:

We’re seeking a Principal Software Engineer to lead the architectural evolution of our platform as we scale to meet growing demand from the world’s largest engineering companies. This is a hands-on technical leadership role where you’ll drive critical architectural initiatives while mentoring our engineering team. You’ll own — in conjunction with the VP of Engineering — the technical vision and execution of our platform’s evolution to a more distributed architecture, making it agentic ready for the next generation of AI applications.

In this role, you will:

• Technical Leadership & Architecture
• Drive the ongoing transition from monolithic to distributed architecture.
• Design and implement architecture to be agentic ready, enabling rapid deployment of AI products and MCP server integrations.
• Own technical decisions balancing immediate business needs with long-term architectural goals.
• Hands-On Development
• Write production-quality Python code for critical platform components.
• Build and optimize distributed compute services.
• Implement reliable workflow orchestration patterns.
• Team Mentorship & Collaboration
• Mentor mid-level developers, elevating the technical capabilities of the entire team.
• Establish engineering best practices and architectural patterns.
• Collaborate with product and business stakeholders to translate requirements into technical solutions.
• Guide technical decision-making and prioritization across the engineering organization.
• Interview and onboard new engineers.

Who You Are:

• 12+ years of software engineering experience with at least 2 years in principal/staff engineering roles.
• Expert-level Python development skills with production experience at scale.
• Deep expertise in distributed systems architecture.
• Strong Kubernetes experience with production workloads.
• Hands-on experience with workflow orchestration tools (Temporal, Airflow, Kubeflow, or similar).
• Cloud platform expertise (AWS required, Azure & GCP beneficial).
• Experience with data processing frameworks (Spark, Athena, Ray, or similar).
• Experience with systems having ML Engineering and MLOps aspects.
• Proven track record of leading architectural transformations in growing companies.
• Excellence in technical communication and stakeholder management.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams — even if you aren’t a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• Technical Excellence: You write clean, maintainable code and design systems that scale.
• Pragmatic Problem-Solver: You balance perfectionism with shipping, making smart trade-offs between short-term delivery and long-term goals.
• Strong Leadership: You proactively identify problems and drive solutions forward.
• Mentorship Mindset: You elevate others through knowledge sharing and patient guidance.
• Ownership Mentality: You take full responsibility for outcomes and drive initiatives to completion.
• Customer Obsession: You understand that our success is measured by our customers’ success.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! 

Senior Engineer

Location: Waterloo, London, England, UK | Hybrid (1 day per week in office)

Who We Are 

At 8th Light, we bring life to the best ideas.

Founded in 2006 and headquartered in Chicago, we are a technology solutions provider that partners with organizations to solve meaningful challenges and drive sustainable growth. From early-stage startups to global enterprises, we work across industries to optimise our clients’ digital products through product strategy innovation, experiential design, AI solutions, and deep engineering expertise. 

Our commitment to quality means we deliver solutions we’re truly proud of, while our curiosity sparks innovation and breakthrough thinking. 8th Lights thrive in an environment that champions continuous education, fueling our growth through mentorship and hands-on work. We foster an open and collaborative culture grounded in honesty that builds trust, and believe true success is measured by the outcomes we create for our clients.

If this kind of work and our kind of people energizes you, you’ve found the right place. 

Who You Are

You’ve shown repeated success on a variety of projects, typically over the course of 4+ years. You have a broad range of expertise that allows you to make an immediate impact on projects. In your previous experience, you have:

• Successfully contributed to high-stakes consulting engagements from discovery to production 
• Written production-quality code using a variety of languages and frameworks, that include: Python, Java, JavaScript, TypeScript, React, Ruby, Scala, R, SQL, and Go
• Built high-quality, maintainable software collaboratively, incrementally, and through an approach tailored towards the unique needs of the clients you’ve served 
• Leveraged AI-assistive development tools for tasks like scaffolding, refactoring, debugging, test generation, and documentation, where appropriate
• Experience building or integrating AI/ML-powered features into products or systems (e.g., recommendation engines, NLP models, computer vision, predictive analytics) 
• Used context-appropriate automated testing to inform software design choices and catch bugs
• Debugged and refactored pre-existing code to incrementally improve it
• Collaborated with teams using Git, MacOS/Linux, and CI/CD
• Remedied architecture-level concerns such as scalability, security, reliability, and performance
• Contributed to forums that encourage idea sharing, collaboration, and problem solving
• Made thoughtful recommendations and set direction in the face of ambiguity
• Mentored and shared knowledge with colleagues
• Actively sought out and effectively given feedback
• Communicated empathically with stakeholders and colleagues
• Influenced stakeholders to balance technical considerations with product and user needs

What You’ll Do At 8th Light

As a senior technologist on projects, you’ll work with a variety of clients, typically one to two in a year, through a variety of technologies and frameworks over the course of your career with us. You’ll work with colleagues who share your passion for technology solutions. You’ll invest time developing your skills and sharing what you know. You’ll be responsible for:

• Making immediate contributions to projects, rapidly building trust with your clients and team
• Working pragmatically to balance technology choices while delivering high-quality work within deadlines
• Contributing to architecture and software design discussions
• Collaborating on systems that involve the full ML lifecycle from data ingestion and preprocessing, to model deployment, integration, and performance monitoring
• Generating new potential solutions to challenges (technical and non-technical) in partnership with team members and clients
• Contributing to formal feedback conversations with teams and clients via retrospectives
• Clearly articulating and documenting outcomes and driving forward action items
• Regular syncs with your delivery team to provide status updates, and for identifying and evaluating risks and presenting potential solutions
• Identifying, mitigating, and resolving blockers to team progress
• Pursuing opportunities to further your skills to grow your career and keep pace with the rapid changes within the technology industry 
• Contributing to your team culture by building connections with your fellow 8th Lights, showing up on camera, and leveraging collaboration opportunities, such as coworking spaces and local team gatherings, where appropriate

Strongly Preferred Skills

We work across many areas, and encourage anyone with the experience listed above to apply. We would particularly like to encourage applicants with experience in the following areas:

• MLOps: including tools like LangChain for application development and managing the ML lifecycle
• Data Engineering: including platforms like Databricks for data processing and analytics
• DevSecOps & DevOps
• Infrastructure as Code

Building a truly diverse, equitable, and inclusive workplace is an ongoing journey, and we’re excited to keep learning and growing together. We have a proud tradition of hiring talented colleagues with real-world career experiences. 

How You’ll be Supported

At 8th Light, we believe our people are our greatest asset. Their growth, well-being, and success shape our future. 

Our wellness package is designed with the Whole YOU in mind and includes:

• A robust L&D programme featuring unlimited access to thousands of books, courses, and expert-led training on the O'Reilly learning platform.
• Coworking support for our global team
• 12 weeks of new parent leave available for eligible employees
• Transparent semi-annual promotion panel

See our full list of Benefits. 

A Note on Compensation

At 8th Light, we are committed to a compensation philosophy that is transparent, fair, and helps us attract and retain top talent in alignment with our company’s strategic growth goals and clients’ needs.

We benchmark our salaries using Geographic Structures to establish competitive pay ranges within the regions where 8th Lights live. Our pay ranges for our Senior Engineer position within London is: £56,640-£70,800 GBP.

Reach out to recruiting@8thlight.com for more relevant information pertaining to your local market.

8th Light Hubs and Geographies

8th Light's culture is rooted in strong connections that extend across our teams, regions, and beyond client work. We are a distributed team across the United States, Canada, and the United Kingdom, with hubs in Chicago, London, Los Angeles, New York, and Seattle. 

• London Co-working: Employees working from our London hub follow a hybrid model, which includes a minimum of one day per week in our Waterloo Office. This co-working day is designed to encourage collaboration and further strengthen our community.In most cases, our consulting engagements do not require travel.

We hope to see you apply! 

_#LI-Hybrid

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

As an AI Engineer at DRW, you will be an integral member of a collaborative multi-asset trading team. You’ll work on high-impact machine learning (ML) and artificial intelligence (AI) initiatives that are central to our business strategy. In this role, you will build critical infrastructure and tooling that leverages AI and ML technology to enhance productivity, efficiency, and discover innovative paths to challenging business and technology problems. Surrounded by cutting-edge technology and experienced trading teams, you will have the opportunity to tackle fascinating new projects while becoming a subject-matter expert in a critical and innovative role.

Key Responsibilities:

• Drive end-to-end development of AI infrastructure and AI driven applications: from initial proof-of-concept to production deployment and ongoing maintenance.
• Collaborate with technologists, traders, quantitative researchers, and data scientists to identify high-impact opportunities for integrating AI and machine learning into technology and business use cases.
• Implement automated systems for continuous training, validation, and monitoring of models, minimizing downtime and ensuring reliability.
• Provide technical leadership in selecting, integrating, and optimizing AI and ML frameworks, libraries, and tools across diverse hardware and software environments.
• Create and maintain feature pipelines, feature stores, and model stores.
• Develop frameworks to enable scalable, reproducible research.
• Proactively troubleshoot performance bottlenecks, conduct root-cause analyses, and implement solutions to optimize GPU or CPU resource usage.

Qualifications:

• Bachelor’s or advanced degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• 3+ years of experience working with machine learning and artificial intelligence technology.
• Strong understanding of core machine learning and artificial intelligence concepts.
• Excellent programming skills in Python.
• Demonstrated experience in building, validating, deploying, monitoring, and updating production ML and AI models.
• Hands-on experience with MLOps and AIOps infrastructure and tooling.
• Proficient in problem-solving and analytical reasoning.
• Exceptional communication and collaboration skills.
• Experience with ML frameworks such as TensorFlow, PyTorch, TensorRT, or ONNX.
• Experience with Large Language Models, including RAG and fine-tuning techniques.
• Familiarity with compute infrastructure necessary to support operating AI and ML technology.

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice.

California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice.

#LI-BL1

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognised brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience. 

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries. 

We are proud of: 

• The work we do and the innovation we drive 
• Our values of share, care and dare 
• A workplace culture that fosters creativity, diversity and autonomy 
• Our borderless, global framework, which enables seamless collaboration 

The role  

We’re looking for a Conversational Analytics Engineer with strong expertise across the Google Cloud Platform ecosystem to drive forward conversational analytics and AI solutions. 

This role blends hands-on engineering, AI/ML innovation and client-facing problem solving. You’ll work across traditional data engineering and emerging LLM / agentic AI patterns, helping design and deploy scalable, production-ready solutions. 

Role responsibilities

Data Engineering, AI & Delivery 

• Design and build scalable data solutions using BigQuery and GCP-native tooling 

• Develop and deploy ML and AI solutions, including LLM-based and agentic systems  

• Work with tools such as Gemini to power conversational and analytical use cases  

• Build and integrate analytical agents into real-world applications  

• Implement evaluation frameworks (version-controlled via Git) to assess model and system performance  

• Orchestrate APIs and enable seamless integration between models, data pipelines, and applications  

• Apply modern MLOps and engineering best practices to deploy and maintain solutions in production  

• Define and assess the quality and timeliness of available data sources 

Problem Solving & Client Engagement 

• Translate business challenges into scalable data and AI solutions  

• Communicate complex technical concepts clearly to non-technical stakeholders  

• Lead client conversations to shape data and analytics solutions, building trust and guiding them through technical and strategic decisions  

• Work closely with cross-functional teams (engineering, product, business)  
• Help shape opportunities where conversational analytics and AI can drive value 

Required Skills

• Strong experience as a Data Engineer / Tech Lead within GCP  

• Deep expertise in BigQuery and cloud-based data architectures  

• Hands-on experience building and integrating ML / AI models into applications  

• Experience with LLMs, RAG, embeddings, or agentic AI systems  

• Strong programming skills (Python, SQL)  

• Experience with API orchestration and system integration  

• Familiarity with evaluation pipelines and version control (Git)  

• Strong communicator who can bridge technical and business teams  

• Curious, pragmatic problem solver with a focus on impact  

• Comfortable working in ambiguity and shaping new AI-driven solutions  

• Collaborative mindset with the ability to guide and influence others 

Nice to have   

• Experience with Gemini, ADK, or similar AI frameworks  
• Exposure to CDPs, analytics tooling, or customer data ecosystems 
• Experience with MLOps and productionising AI solutions  

If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn. 

Commitment to reaching all kinds of people 

We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all. 

The benefits  

This is a full time position based in the UK. 

Beyond a competitive compensation package, we offer: 

• Flexibility, with remote and hybrid work options (country-dependent) 
• Career advancement, with international mobility and professional development programs 
• Learning and development, with access to cutting-edge tools, training and industry experts 

Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process.   

Your application process

Once you apply, our Talent Acquisition team will review your application. Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential.

⚠️ Beware of recruitment fraud!

We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know. 

About Valtech

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world. 

At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more. 

At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate. 

Are you ready to create what’s next? Join us.

Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning. 

Spectrum collects data from an organization’s code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that’s extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.

Spectrum is a resident of JetBrains' startup incubator, with startup speed and autonomy, and backed by 25 years of developer tooling expertise. We are looking for a top-class ML Engineer who will help us shape the future of software development. You will own our AI and ML engineering stack and help define the research agenda for our team. Your technical vision and design decisions will directly shape the product and determine its success.

Your responsibilities will include:

• Designing and building the ML/LLM solution for data ingestion, knowledge extraction, retrieval, and subsequent reasoning.
• Creating the datasets, metrics, and pipelines that drive measurable improvements across the system.
• Architecting and improving agents for context retrieval, knowledge extraction, and data alignment, which includes prompt engineering, model selection, and inference optimization.
• Establishing MLOps practices, including orchestration, observability, and experiment tracking.
• Collaborating with the engineering team on system design and with JetBrains Research on the research agenda.
• Defining hiring criteria, growing the ML team, and shaping the ML team culture.

We expect you to have:

• A proven track record as an ML/AI Lead.
• At least five years of experience in ML/AI systems, with at least two years focused on LLMs and generative AI.
• A deep understanding of the LLM ecosystem, including model architectures and fine-tuning approaches.
• Hands-on experience with:
• Prompt engineering and LLM pipeline design, including evaluation.
• Agentic frameworks such as LangChain, LlamaIndex, LangSmith, smolagents, or an equivalent.
• Vector databases and retrieval-augmented generation (RAG) patterns.
• Deploying and scaling LLM-powered applications using APIs (e.g. OpenAI or Anthropic) or open-source models.
• Strong Python skills – Kotlin knowledge would be a plus.
• Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Proficiency in English, both written and verbal. 

Our ideal candidate would have:

• Experience with ontologies, knowledge graphs, or graph-based reasoning.
• Experience in early-stage startups – you enjoy the zero-to-one phase.
• The ability to think strategically about product-led AI, beyond just training models in isolation.
• A background in code analysis, developer tools, or software engineering research.
• Experience with multi-agent systems or complex agentic workflows.
• Actively contributed to relevant open-source projects or publications.

What we offer

• A competitive salary and JetBrains benefits.
• A generous runway and corporate resources with startup autonomy.

#LI-KP1

Flow Traders is looking for a Senior Research Engineer to join us in our London office. This is a unique opportunity to join a leading proprietary trading firm with an entrepreneurial and innovative culture at the heart of its business. We value quick-witted, creative minds and challenge them to make full use of their capacities. 

As a Senior Research Engineer, you will be responsible for helping to lead the development of our trading model research framework and using it to conduct research to develop models for trading in production. You'll expand the framework to become global standard way of training, consuming, combining, and transforming any data source in a data-driven systematic way. You will then partner with Quantitative Researchers to build the trading models themselves.

What you will do

• Help to lead the development and global rollout of our research framework for defining and training models through various optimization procedures (supervised learning, backtesting etc.), as well as its integration with our platform for deploying and running those models in production
• Partner with Quantitative Researchers to conduct research: test hypotheses and tune/develop data-driven systematic trading strategies and alpha signals

What you need to succeed

• Advanced degree (Master's or PhD) in Machine Learning, Statistics, Physics, Computer Science or similar
• 8+ years of hands-on experience MLOps, Research Engineering, or ML Research
• A strong background in mathematics and statistics
• Strong proficiency in programming languages such as Python, with experience in libraries like numpy, pytorch, polars, pandas, and ray
• Demonstrated experience in designing and implementing end-to-end machine learning pipelines, including data preprocessing, model training, deployment, and monitoring
• Understanding of and experience with modern software development practices and tools (e.g. Agile, version control, automated testing, CI/CD, observability)
• Understanding of cloud platforms (e. g., AWS, Azure, GCP) and containerization technologies (e. g., Docker, Kubernetes)

Flow Traders does not accept unsolicited resumes from any professional staffing or search firms. All resumes, and any other information identifying potential candidates, submitted to any employee at Flow Traders via-email, the Internet or directly without a valid and signed search agreement will be deemed free to contact by Flow Traders without any restrictions and no placement fee of any kind will be paid in the event the candidate is hired by Flow Traders.

Note: We are currently recruiting for multiple positions across different levels, however please only apply for the role that best aligns with your skillset and career goals.

What you will do 

• Work closely with our research scientists and simulation engineers to build and deliver models that address real-world physics and engineering problems.
• Design, build and optimise machine learning models with a focus on scalability and efficiency in our application domain.
• Transform prototype model implementations to robust and optimised implementations.
• Implement distributed training architectures (e.g., data parallelism, parameter server, etc.) for multi-node/multi-GPU training and explore federated learning capacity using cloud (e.g., AWS, Azure, GCP) and on-premise services.
• Work with research scientists to design, build and scale foundation models for science and engineering; helping to scale and optimise model training to large data and multi-GPU cloud compute.
• Identify the best libraries, frameworks and tools for our modelling efforts to set us up for success.
• Own Research work-streams at different levels, depending on seniority.
• Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems.
• Work at the intersection of data science and software engineering to translate the results of our Research into re-usable libraries, tooling and products.
• Foster a nurturing environment for colleagues with less experience in ML / Engineering for them to grow and you to mentor.

What you bring to the table

• Enthusiasm about developing machine learning solutions, especially deep learning and/or probabilistic methods, and associated supporting software solutions for science and engineering.
• Ability to work autonomously and scope and effectively deliver projects across a variety of domains.
• Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.
• Excellent collaboration and communication skills — with teams and customers alike.
• MSc or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, software engineering, or a related field, with a record of experience in any of the following:
  
  • Scientific computing;
  • High-performance computing (CPU / GPU clusters);
  • Parallelised / distributed training for large / foundation models.
• Ideally >2 years of experience in a data-driven role in a professional setting, with exposure to:
  • scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus);
  • distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton);
  • cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP);
  • building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications;
  • C/C++ for computer vision, geometry processing, or scientific computing;
  • software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps);
  • container-ization and orchestration (Docker, Kubernetes, Slurm);
  • writing pipelines and experiment environments, including running experiments in pipelines in a systematic way.

What we offer

Build what actually matters

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 you’re ambitious, thoughtful, and driven by impact, you’ll 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 isn’t just welcomed, it’s 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 doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

🏦 10% employer pension contribution - because investing in future matters.

🍽️ 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.

☀️ 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, we’re continuing to build this as we grow…

Note: We are currently recruiting for multiple positions across different levels, however please only apply for the role that best aligns with your skillset and career goals.

What you will do 

• Shape Research group strategy and culture in a significant way, especially in domains of expertise.
  • Be opinionated and formulate strategy on engineering topics relevant to our Research priorities, especially on: scaled engineering, securing compute, infrastructure stack.
  • Define necessary profiles to execute this strategy.
  • Promote effective working patterns and proactively flag issues with team dynamics to foster a productive environment.
  • Nurture younger colleagues to grow their skillset and guide their professional development.
• Own Research work-streams at a high-level to deliver outcomes.
  • Align priorities with problem stakeholders, internal and external.
  • Set the technical direction for the stream and apply judgement and taste to drive progress.
  • Plan roadmaps with clear milestones for key decisions and outcomes.
  • Organise and guide the more junior members of the team to effectively execute and deliver against this roadmap.
  • Communicate purpose and key outcomes to raise awareness across the company and create opportunities for use and deployment.
• The below activities in particular.
  • Work closely with our research scientists and simulation engineers to build and deliver models that address real-world physics and engineering problems.
  • Design, build and optimise machine learning models with a focus on scalability and efficiency in our application domain.
  • Transform prototype model implementations to robust and optimised implementations.
  • Implement distributed training architectures (e.g., data parallelism, parameter server, etc.) for multi-node/multi-GPU training and explore federated learning capacity using cloud (e.g., AWS, Azure, GCP) and on-premise services.
    • Work with research scientists to design, build and scale foundation models for science and engineering; helping to scale and optimise model training to large data and multi-GPU cloud compute.
  • Identify the best libraries, frameworks and tools for our modelling efforts to set us up for success.
  • Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems.
  • Work at the intersection of data science and software engineering to translate the results of our Research into re-usable libraries, tooling and products.
  • Foster a nurturing environment for colleagues with less experience in ML / Engineering for them to grow and you to mentor.

What you bring to the table

• Enthusiasm about developing machine learning solutions, especially deep learning and/or probabilistic methods, and associated supporting software solutions for science and engineering.
• Ability to work autonomously and scope and effectively deliver projects across a variety of domains.
• Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.
• Excellent collaboration and communication skills — with teams and customers alike.
• MSc or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, software engineering, or a related field, with a record of experience in any of the following:
  • scientific computing;
  • high-performance computing (CPU / GPU clusters);
  • parallelised / distributed training for large / foundation models.
•  4 years of experience in a data-driven role in a professional industry setting, where you have been instrumental in most of the below:
  • • scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus);
    • employing distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton);
    • employing cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP);
    • building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications;
    • building or using C/C++ for computer vision, geometry processing, or scientific computing;
    • following and promoting software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps);
    • container-izing and orchestrating compute tasks (Docker, Kubernetes, Slurm);
    • writing pipelines and experiment environments, including running experiments in pipelines in a systematic way.

What we offer

Build what actually matters

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 you’re ambitious, thoughtful, and driven by impact, you’ll 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 isn’t just welcomed, it’s 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 doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

🏦 10% employer pension contribution - because investing in future matters.

🍽️ 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.

☀️ 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, we’re continuing to build this as we grow…

Why Engineering at Dataiku?

Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here.

Here are some useful links so you preview what we do at Dataiku: Dataiku's Key Capabilities ; Dataiku's Github, you can also take a look at the Gallery, a public instance showcasing some example projects (note editing is very limited and will be regularly reset). 

Our product is called Dataiku DSS which stands for Dataiku Data Science Studio. If you’d like to know more about it, you can watch the demo here or try the free version here.

How you’ll make an impact

This position is either onsite/hybrid from our London office or full remote from any part of the UK.

As a Fullstack Engineer, you’ll contribute to building Dataiku DSS core features by joining one of the following themes:

• Data Preparation: Develop tools for data integration, transformation, and cataloging, as well as Jupyter notebooks, SQL workbenches, and APIs.
  • Add new capabilities for data integration, transformation, and visualization using LLMs
  • Optimize workflows for large-scale datasets and improve database support
  • Strengthen developer tools like Jupyter notebooks and SQL workbenches
  • Tech stack: Java, Python, AngularJS, Angular

• AI & Machine Learning: Collaborate on next-gen AI features, from statistics and time series forecasting to LLM inference.
• Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models
• Collaborate with research teams on innovative machine learning experiments
• Tech stack: Python, scikit-learn, TensorFlow, PyTorch, Java, Angular, AngularJS

• Data Consumption: build the experience that makes data accessible and actionable for everyone.
  • Enhance our collaborative Workspaces to organize and explore charts, dashboards, datasets and more
  • Create innovative interfaces that answer business questions and surface relevant insights using LLMs
  • Tech stack: Angular, AngularJS, Java, Python

• Data Visualization: elevate our data visualization capabilities with high-performance charting tools and dashboards.
  • Develop new chart types and optimize visualization performance
  • Enhance dash boarding capabilities to deliver fast and flexible experiences
  • Tech stack: React, AngularJS, Angular, D3.js, ECharts, Node.js, Java, Spring

• MLOps: Develop back-end capabilities for automating and monitoring ML model lifecycles while supporting cross-functional collaboration.
  • Build tools to automate retraining, monitoring, and deployment of ML models
  • Enhance collaboration features for ML stakeholders
  • Tech stack: Python, Java, Angular, Angular.JS, Kubernetes, Docker
    
    
• Platform: Focus on scaling and securing the platform while improving cloud integrations and supporting a wide array of data sources and engines.
  • Optimize processing engines for scalability and latency
  • Expand capabilities to support new databases and cloud platforms
  • Tech stack: Java, Python, Angular, Kubernetes, Spark, AWS, Azure, GCP
    
    
• AI Governance: Build features for AI compliance, connecting disparate systems and simplifying governance processes.
  • Develop customizable platforms for managing AI compliance and governance
  • Simplify policy enforcement and integration across disparate systems
  • Tech stack: Java, Angular, PostgreSQL

What you need to be successful 

• We’re stack agnostic, so all you need is a significant experience in software engineering,  building a real product
• We’re hiring at all levels (junior, mid, senior)
• A passion for combining backend performance with exceptional frontend user experience.
• You want to work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challenges at scale

What does the hiring process look like?

• Initial call with a member of our Technical Recruiting team (45min)
• Video call with an Engineering Team Lead (1h30)
• Technical Assessment to show your skills (Home Test or Live Coding)
• Final Interviews with our VPs of Engineering (2h)   #LI-Remote

Who we are

• Artefact is a leading global consulting firm dedicated to accelerating the adoption of data and AI. We work with a variety of businesses, from supermarket chains, to private equity firms and telecoms; including Nissan, L'Oréal, Carrefour, WHSmith, Orange, Beiersdorf, BNP Paribas, and Samsung.
• Our success stems from combining advanced data technologies, agile methods for quick delivery, and dedicated teams of data scientists, data engineers, business consultants, and data analysts.
• Our 1,800 employees operate in 25 countries (Americas, Europe, Asia, Middle East, India, Africa) and we partner with 1,000+ clients.

What you will be doing

As a Junior Engineer in our London office, your role will encompass:

• working on engineering projects together with senior team members
• training and certification to enhance your skills in software engineering, data science, and data architecture. 

Qualifications

Necessary education and experience

• Education: A Bachelor's or Master’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative field.
• Programming Proficiency: Strong programming skills in Python and a solid understanding of data structures and algorithms.
• Software Engineering Fundamentals: A demonstrable understanding of version control and repository tools (Git, CI/CD) and a commitment to writing clean, well-documented code.
• Data Skills: Experience with SQL for querying relational databases.
• Problem-Solving Skills: An analytical mindset with the ability to break down complex problems into manageable steps.
• Eagerness to Learn: A genuine passion for technology and a proactive attitude towards self-development and learning new skills, as demonstrated through projects or coursework.
• Communication & Collaboration: Strong verbal and written communication skills, with the ability to work effectively in a team environment and learn from senior members.

Desirable experience

• Cloud and MLOps Exposure: Basic familiarity with a cloud platform (AWS, GCP, or Azure) and an awareness of concepts like containerization (Docker).
• Core ML Knowledge: A good grasp of fundamental machine learning concepts, including supervised/unsupervised learning, model evaluation techniques, and feature engineering.
• Advanced Education: A Master's degree or PhD in a relevant field is a strong plus.

Please send your CV to hr-uk@artefact.com

Who we are

• Artefact is a leading global consulting firm dedicated to accelerating the adoption of data and AI. We work with a variety of businesses, from supermarket chains, to private equity firms and telecoms; including Nissan, L'Oréal, Carrefour, WHSmith, Orange, Beiersdorf, BNP Paribas, and Samsung.
• Our success stems from combining advanced data technologies, agile methods for quick delivery, and dedicated teams of data scientists, data engineers, business consultants, and data analysts.
• Our 1,800 employees operate in 25 countries (Americas, Europe, Asia, Middle East, India, Africa) and we partner with 1,000+ clients.

What you will be doing

As a Senior Data Scientist in our London office, your role will encompass:

• Designing and implementing advanced data science and machine learning solutions to solve complex business problems.
• Taking ownership of project streams, from defining technical deliverables and timelines to presenting updates to client steering committees.
• Supervising and mentoring team members on code, deployment, and best practices.
• Architecting and deploying robust, scalable solutions using modern cloud technologies and MLOps principles.

Qualifications

Necessary education and experience

• Education: A Bachelor's or Master’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative field.
• Project & Team Leadership: Demonstrable experience supervising team members, taking responsibility for project delivery, defining technical tasks, and presenting project updates to both internal and client stakeholders.
• Advanced Modelling: Proven ability to implement a range of complex models such as time-series forecasting, gradient boosting, clustering, NLP, and Bayesian inference.
• ML-Ops & Orchestration: Strong experience with MLOps tools for orchestration, experiment tracking, hyper-parameter tuning, and deploying automated model retraining pipelines.
• Programming & Data Engineering: Proficiency in object-oriented Python, advanced dataframes (Polars/Pyspark), and data versioning (DVC). Experience designing data storage solutions and using object-oriented SQL interfaces.
• Cloud & DevOps: Hands-on experience with at least two major cloud providers (AWS, Azure, GCP), including app deployment, database services (e.g., RDS, CosmosDB), and infrastructure-as-code (Terraform). Solid understanding of CI/CD for testing and containerisation.

Desirable experience

• Advanced Education: A Master's degree or PhD in a relevant field is a strong plus.
• Parallelisation & Performance: Experience with parallelisation frameworks like Pyspark or Ray.
• Advanced Cloud & Infrastructure: Familiarity with serverless deployments (e.g., Fargate, Lambdas), infrastructure automation with Terratest or Ansible.

Please send your CV to hr-uk@artefact.com

Who we are

• Artefact is a leading global consulting firm dedicated to accelerating the adoption of data and AI. We work with a variety of businesses, from supermarket chains, to private equity firms and telecoms; including Nissan, L'Oréal, Carrefour, WHSmith, Orange, Beiersdorf, BNP Paribas, and Samsung.
• Our success stems from combining advanced data technologies, agile methods for quick delivery, and dedicated teams of data scientists, data engineers, business consultants, and data analysts.
• Our 1,700 employees operate in 25 countries (Americas, Europe, Asia, Middle East, India, Africa) and we partner with 1,000+ clients.

What you will be doing

As a Junior Software Engineer in our London office, your role will encompass:

• working on engineering projects together with senior team members
• training and certification to enhance your skills in software engineering, data science, and data architecture.

Qualifications

Necessary education and experience

• Education: A Bachelor's or Master’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative field.
• Programming Proficiency: Strong programming skills in Python and a solid understanding of data structures and algorithms.
• Software Engineering Fundamentals: A demonstrable understanding of version control and repository tools (Git, CI/CD) and a commitment to writing clean, well-documented code.
• Data Skills: Experience with SQL for querying relational databases.
• Problem-Solving Skills: An analytical mindset with the ability to break down complex problems into manageable steps.
• Eagerness to Learn: A genuine passion for technology and a proactive attitude towards self-development and learning new skills, as demonstrated through projects or coursework.
• Communication & Collaboration: Strong verbal and written communication skills, with the ability to work effectively in a team environment and learn from senior members.

Desirable experience

• Cloud & MLOps Exposure: Basic familiarity with a cloud platform (AWS, GCP, or Azure) and an awareness of concepts like containerization (Docker).
• Core ML Knowledge: A good grasp of fundamental machine learning concepts, including supervised/unsupervised learning, model evaluation techniques, and feature engineering.
• Advanced Education: A Master's degree or PhD in a relevant field is a strong plus.

Hybrid working pattern 

Who we are

• Artefact is a leading global consulting firm dedicated to accelerating the adoption of data and AI. We work with a variety of businesses, from supermarket chains, to private equity firms and telecoms; including Nissan, L'Oréal, Carrefour, WHSmith, Orange, Beiersdorf, BNP Paribas, and Samsung.
• Our success stems from combining advanced data technologies, agile methods for quick delivery, and dedicated teams of data scientists, data engineers, business consultants, and data analysts.
• Our 1,800 employees operate in 25 countries (Americas, Europe, Asia, Middle East, India, Africa) and we partner with 1,000+ clients.

What you will be doing

As a Senior Data Scientist in our London office, your role will encompass:

• Designing and implementing advanced data science and machine learning solutions to solve complex business problems.
• Taking ownership of project streams, from defining technical deliverables and timelines to presenting updates to client steering committees.
• Supervising and mentoring team members on code, deployment, and best practices.
• Architecting and deploying robust, scalable solutions using modern cloud technologies and MLOps principles.

Qualifications

Necessary education and experience

• Education: A Bachelor's or Master’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative field.
• Project & Team Leadership: Demonstrable experience supervising team members, taking responsibility for project delivery, defining technical tasks, and presenting project updates to both internal and client stakeholders.
• Advanced Modelling: Proven ability to implement a range of complex models such as time-series forecasting, gradient boosting, clustering, NLP, and Bayesian inference.
• ML-Ops & Orchestration: Strong experience with MLOps tools for orchestration, experiment tracking, hyper-parameter tuning, and deploying automated model retraining pipelines.
• Programming & Data Engineering: Proficiency in object-oriented Python, advanced dataframes (Polars/Pyspark), and data versioning (DVC). Experience designing data storage solutions and using object-oriented SQL interfaces.
• Cloud & DevOps: Hands-on experience with at least two major cloud providers (AWS, Azure, GCP), including app deployment, database services (e.g., RDS, CosmosDB), and infrastructure-as-code (Terraform). Solid understanding of CI/CD for testing and containerisation.

Desirable experience

• Advanced Education: A Master's degree or PhD in a relevant field is a strong plus.
• Parallelisation & Performance: Experience with parallelisation frameworks like Pyspark or Ray.
• Advanced Cloud & Infrastructure: Familiarity with serverless deployments (e.g., Fargate, Lambdas), infrastructure automation with Terratest or Ansible.

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience.

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.

We are proud of:

• The work we do and innovation we drive
• Our Values of share, care and dare
• A workplace culture that fosters creativity, diversity and autonomy
• Our borderless, global framework, which enables seamless collaboration

The Role:

As a Lead Data Scientist, you bring strong commercial experience applying data science to solve real-world business challenges. You are comfortable working across classical machine learning and emerging AI techniques, particularly in LLM/Agentic AI space.

You can move between hands-on modelling, exploring new approaches (e.g. LLMs), and explaining insights clearly to non-technical stakeholders. With a pragmatic, problem-solving mindset, you help shape opportunities and deliver impactful solutions.

You will thrive in this role if you are:

• A curious problem solver who challenges the status quo
• Comfortable bridging the gap between technical data science and client business needs
• Passionate about innovation and exploring “what’s next” in AI and ML
• Experienced in working within Agile methodologies and consultancy environments
• Keen to take ownership while supporting and guiding others

Role Responsibilities:

Data Science, AI & Delivery

• Work with structured and unstructured data to support model development and analysis
• Design and implement ML and AI solutions, including LLM-based and traditional approaches
• Apply techniques such as RAG, embeddings, and fine-tuning where appropriate
• Contribute to development and optimization of AI applications using established and emerging agentic patterns (e.g. tool use, orchestration, multi-step reasoning)
• Apply evaluation frameworks to assess model and system performance
• Contribute to deploying models and supporting them in production using engineering and MLOps best practices
• Stay up to date with emerging AI techniques and experiment with new approaches, tools, and frameworks

Problem Scoping & Client Engagement

• Translate business questions into clear data science approaches
• Communicate results and insights to technical and non-technical stakeholders
• Contribute to identifying opportunities where data science and AI can add value
• Support project scoping and provide guidance to less experienced team members when needed

Must have Qualifications:

• 5+ years of experience in Data Science or Analytics
• Strong foundation in machine learning and predictive modelling
• Exposure to Generative AI concepts (e.g. LLMs, RAG, fine-tuning, prompt engineering)
• Strong programming skills in Python and SQL
• Familiarity with cloud-based solutions (e.g. GCP, Azure, AWS)
• Experience working with real-world, production data problems
• Ability to communicate technical concepts clearly to non-technical stakeholders

Nice to have Qualifications:

• Experience in consulting or client-facing environments
• Hands-on experience designing and deploying Generative AI solutions, including Agentic AI systems.
• Experience with MLOps practices and taking models into production environments
• Exposure to modern data engineering practices and integration with data pipelines
• Awareness of Responsible AI practices (bias, evaluation, safety)

If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn.

Commitment to reaching all kinds of people

We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all.

Your application process

Once you apply, our Talent Acquisition team will review your application. If your skills and experience align with the role, we’ll reach out for next steps.

⚠️ Beware of recruitment fraud: Only engage with official Valtech email addresses ending in @valtech.com.

We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know.

About Valtech

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world.

At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more.

At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate.

Are you ready to create what’s next? Join us.

Miro is looking for a Machine Learning Research Engineer to serve as the technical "North Star" for our Machine Learning organization. You will operate as an Individual Contributor, driving the architectural decisions behind the "Intelligent Canvas."

Your challenge is unique in the industry: You are not just processing text. You are building models that understand spatial relationships, visual diagrams, and unstructured collaboration. You will research, prototype, and ship novel architectures that combine Large Language Models (LLMs), Computer Vision, and Graph Neural Networks (GNNs) to make Miro the smartest collaboration platform on earth.

What you’ll do

• Design, train, and ship production-grade ML models—including deep learning, NLP, and computer vision systems—that solve complex business problems and power core product features.
• Conduct deep exploratory research on massive datasets to uncover novel patterns in user behavior and content creation, translating raw data insights into new predictive modeling opportunities.
• Apply advanced fine-tuning strategies (e.g., PEFT, LoRA) to adapt state-of-the-art foundation models to specific domain tasks, rigorously experimenting to maximize performance.
• Architect scalable ML pipelines for data processing, feature engineering, training, and evaluation, ensuring high data quality and system reliability.
• Optimize model performance for latency, throughput, and resource utilization, balancing model complexity with production constraints (e.g., overfitting vs. underfitting, compute efficiency).
• Collaborate cross-functionally with data engineers, product managers, and software engineers to translate business requirements into technical ML specifications and integrate models into user-facing applications44.
• Champion MLOps excellence by automating deployment workflows, implementing CI/CD for ML, and establishing robust monitoring for model drift and health.
• Stay at the forefront of ML research, evaluating novel algorithms and techniques (e.g., Transformer architectures, quantization) to drive innovation and technical strategy.

What you’ll need

• Strong foundation in ML theory and statistics, including hypothesis testing, probability distributions, regression, classification, and optimization techniques.
• Solid engineering fundamentals. You are comfortable writing production-level Python and have a deep understanding of data structures, algorithms, and distributed system design.
• Deep proficiency in Python and the modern ML stack, with hands-on experience using libraries like Pandas, NumPy, Scikit-learn, and deep learning frameworks (PyTorch, TensorFlow).
• Gradient Debugging: Expertise in PyTorch or JAX, including experience with distributed training (e.g., DDP, FSDP) and debugging complex gradient issues.
• Applied Research: Ability to read, implement, and improve upon the latest academic papers (NeurIPS, ICML, CVPR). You don't just use libraries; you understand the math underneath them and can reproduce results in peer-reviewed papers.
• Track record of end-to-end ML delivery, from exploratory data analysis (EDA) and feature engineering to training, validation, and deploying models in a production environment.
• Experience with large-scale systems, capable of designing resilient architectures that handle vast datasets and high-throughput inference requests.
• Strong engineering mindset, valuing code quality, testing, modularity, and maintainability just as highly as model accuracy.

Education + Experience

• Option A: Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related field plus ~3+ years of professional ML engineering experience.
• Option B: No formal degree, ~6+ years of industry experience demonstrating equivalent proficiency in building and shipping ML systems.

What's in it for you

LON:

• Competitive equity package
• Health insurance for you and your family
• Corporate pension plan
• Lunch, snacks and drinks provided in the office
• Wellbeing benefit and WFH equipment allowance
• Annual learning and development allowance to grow your skills and career
• Opportunity to work for a globally diverse team
  

Multi Location: Amsterdam / Berlin / Yerevan / London:

• Competitive equity package
• Lunch, snacks and drinks provided in the office
• Wellbeing benefit and WFH equipment allowance
• Annual learning and development allowance to grow your skills and career
• Opportunity to work for a globally diverse team

Recruiter: #LI-MH1

Req ID: CSQ327R44

Location: Hybrid – London

We’re hiring for multiple roles within our Professional Services team. Depending on experience and scope, this position may be offered as Senior Solutions Consultant, Resident Solutions Architect, or Senior Resident Solutions Architect.

You may know this role as a Big Data Solutions Architect, Analytics Architect, Data Platform Architect, or Technical Consultant. The final title will align to your experience, technical depth, and customer-facing ownership.

As a Big Data Solutions Architect (Internal Title - Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium-term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of  professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• Extensive experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps 
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 10% of the time
• [Preferred] Databricks Certification but not essential

CSQ327R39

We’re hiring for multiple roles within our Professional Services team. Depending on experience and scope, this position may be offered as a Senior Solutions Consultant or a Resident Solutions Architect.

You may know this role as a Big Data Solutions Architect, Analytics Architect, Data Platform Architect, or Technical Consultant. The final title will align to your experience, technical depth, and customer-facing ownership.

As a Data Platform Solutions Architect (Internal Title - Resident Solutions Architect) on our Professional Services team for the Emerging Enterprise & Digital Natives business in EMEA, you will work with clients on short to medium-term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• Drive high-impact customer projects: Design and build reference architectures, implement production use cases, and create “how-to” guides tailored to the unique needs of fast-moving Emerging Enterprise & Digital Native customers in EMEA.
• Collaborate on project scoping: Work closely with Engagement Managers and customers to define project scope, schedules, and deliverables for professional services engagements.
• Enable transformational initiatives: Guide strategic customers through their end-to-end big data journeys—migrating from legacy platforms and deploying industry-leading data and AI applications on the Databricks platform.
• Consult on architecture & design: Provide thought leadership on solution design and implementation strategies, ensuring customers can successfully evaluate and adopt Databricks.
• Offer advanced support: Serve as an escalation point for operational issues, collaborating with Databricks Support and Engineering to resolve challenges quickly.
• Align technical delivery: Partner with cross-functional Databricks teams (Technical, PM, Architecture, and Customer Success) to align on milestones, ensuring customer needs and deadlines are met.
• Amplify product feedback: Provide implementation insights to Databricks Product and Support teams, guiding rapid improvements in features and troubleshooting for customers.

What we look for:

• Extensive experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps 
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 10% of the time
• [Preferred] Databricks Certification but not essential

REQ ID: FEQ127R254

Location: Hybrid – London

We’re hiring for multiple roles within our Professional Services team. Depending on experience and scope, this position may be offered as Senior Solutions Consultant, Resident Solutions Architect, or Senior Resident Solutions Architect.

You may know this role as a Big Data Solutions Architect, Analytics Architect, Data Platform Architect, or Technical Consultant. The final title will align to your experience, technical depth, and customer-facing ownership.

As a Big Data Solutions Architect (Internal Title - Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium-term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of  professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• Extensive experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps 
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 10% of the time
• [Preferred] Databricks Certification but not essential

Req ID: CSQ127R149

Location: United Kingdom Remote with occasional travel to the London office and clients' sites.

We’re hiring for multiple roles within our Professional Services team. Depending on experience and scope, this position may be offered as Senior Solutions Consultant, Resident Solutions Architect, or Senior Resident Solutions Architect.

You may know this role as a Big Data Solutions Architect, Analytics Architect, Data Platform Architect, or Technical Consultant. The final title will align to your experience, technical depth, and customer-facing ownership.

As a Resident Solutions Architect in our Professional Services team you will work with clients on short to medium-term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of  professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• Extensive experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps 
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 10% of the time
• [Preferred] Databricks Certification but not essential

At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the world’s most robust and effective developer tools. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

We are working on an ambitious new platform that provides AI capabilities to all JetBrains products. Our platform is based on models developed in-house for writing and coding assistance, as well as integration with our strategic partners.

We are looking for a Research Engineer who can contribute to training foundation models for coding tasks. You’ll be working on developing Large Language Models from scratch and deploying them into production environments where they will be accessible by end users across the globe.

We value engineers who: 

• Can plan projects and make decisions independently, consulting with others if needed.
• Identify customer needs and prioritize their tasks accordingly.
• Start with the simplest solutions and gradually add complexity as needed.
• Take sole responsibility for an entire subsystem.
• Have a passion for learning and a desire to stay up to date with the latest developments in the LLM field.

In this role, you will: 

• Work with stakeholders to convert business requirements into technical specifications.
• Train LLMs from scratch on a large GPU cluster.
• Collect and process pre-training and fine-tuning datasets.
• Support and improve existing subsystems.

We’ll be happy to have you on our team if you have: 

• Experience in design, deployment, and support of production ML systems.
• A strong theoretical background in NLP and transformer-based approaches.
• Proficiency with modern deep learning frameworks such as PyTorch and common libraries for NLP.
• Experience in distributed training of multi-billion parameter models.
• Attention to detail in everything you do and great communication skills.

We’d be especially thrilled if you have experience with: 

• LLM inference frameworks such as vLLM, DeepSpeed, TensorRT.
• LLM alignment techniques such as RLHF/RLAIF.
• MLOps tools and practices, including CI/CD for ML.
• K8s and Kubeflow.
• Scientific publications in the NLP field.

How we develop JetBrains AI: 

• A cluster of hundreds of NVIDIA GPUs as training infrastructure.
• Git for source control management.
• Python, PyTorch, and HuggingFace as an ML stack.
• Kubeflow and Weights & Biases for experiment tracking.
• TeamCity as a CI Automation system.

#LI-KP1

At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the world’s most robust and effective developer tools. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

JetBrains is evolving beyond standalone developer tools toward a unified, AI-native platform for software development.

AI is no longer just an assistant inside the editor – it is becoming an active participant in how software is planned, built, reviewed, and operated across teams and organizations. This shift introduces new challenges that cannot be solved at the level of individual tools alone: governance, security, cost control, observability, and coordinated work between humans and autonomous agents.

Our goal is to build a platform that enables companies to adopt AI in software development in a structured, scalable, and economically efficient manner without locking them into closed ecosystems. This platform will serve as the execution and governance layer for AI-driven development, deeply integrated with developer tools but designed to work across teams, products, and environments.

We are looking for an experienced ML leader who has created products with an ML backbone, weaving together research, technical excellence, and strong product focus.

We are seeking a professional who excels in three key areas: technology, product vision, and business operations. This role involves extensive cooperation with products across the company – both AI-native and just integrating AI.

In this role, you will: 

• Identify, prioritize, and champion high-impact AI projects that align with JetBrains' product strategy and deliver measurable business value.
• Lead a team of about 50 people across multiple AI initiatives, including hiring and developing team leads, ML engineers, and MLOps specialists.
• Set the technical direction for JetBrains’ ML roadmap,  translating cutting-edge AI advancements into practical product innovations.
• Ensure projects deliver on commitments and create measurable value.
• Set technical standards, architectural direction, and best practices for ML development.

We’ll be happy to have you on our team if you have: 

• The ability to balance long-term R&D with short-term product needs.
• A track record of shipping production ML systems that users actually use.
• Experience building business cases for technical projects.
• A deep understanding of modern ML infrastructure, LLMs, and AI tooling.
• Outstanding stakeholder management skills and are comfortable working with senior leaders.
• The ability to thrive in a fast-paced environment, effectively managing multiple projects simultaneously.
• Excellent management and communication skills.
• Attention to detail in everything you do.

We’d be especially thrilled if you have experience with: 

• Distributed training of multi-billion parameter models.
• CI systems, workflow automation, and experiment tracking.
• The Kotlin programming language.

#LI-KP1 #LI-HYBRID

We are hiring a Principal Machine Learning Engineer to work on cutting-edge R&D and translating research into customer-centric solutions.   

As innovators in speech technology, our mission is to Understand Every Voice—a vision that has propelled us to be world leaders of Voice AI. Fuelled by innovation, inclusivity, and a passion for making a global impact through world-leading Speech AI, we're looking for an experienced Principal Machine Learning Engineer to accelerate our efforts towards exceptional speech solutions. 

Our Modelling Team trains diverse models, including large self-supervised ones, supporting Speechmatics towards being the most accurate speech recognition system globally. It also ensures their deployment into production, working with the latest developments in ML, but also with the best engineering practices for software engineering and model serving. 

This is a hands-on, technical leadership role with high ownership.  You will develop and deploy advanced speech systems that power our products as well as co-define the technical vision for ML, drive innovation, and mentor engineering teams. Your work will span the entire codebase.    

What You’ll Do:

• Develop and deploy ML models, translating research into scalable, maintainable code and services 
• Optimise ML models for speed, accuracy, and cost efficiency 
• Evaluate and integrate cutting-edge approaches into our ML stack
• Identify and solve complex ML problems across the organisation
• Define and enforce best practices for code quality, model lifecycle management, etc.
• Mentor engineers and foster a culture of technical excellence and innovation
• Co-define the long-term technical vision 

What We’re Looking For:

• Deep understanding of the modern Machine Learning stack, for example:
  • Knowledge of contemporary transformer architectures (e.g., GQA, KV-caching) and best practices
  • Expertise in distributed training techniques
  • Familiarity with optimisation strategies for model inference (e.g., dynamic batching, flash attention, speculative decoding)
• Proven track record of developing and deploying models at scale
• Expertise in Python, ML frameworks (TensorFlow, PyTorch), and experience with cloud platforms
• Strong familiarity with MLOps principles, CI/CD pipelines, and containerization (Docker, Kubernetes)

  With preferred backgrounds covering some of the following:

• Experience with speech-to-text or text-to-speech 
• Contributions to open-source projects or published research in top-tier conferences

We are hiring a Principal Machine Learning Engineer to work on cutting-edge R&D and translating research into customer-centric solutions.   

As innovators in speech technology, our mission is to Understand Every Voice—a vision that has propelled us to be world leaders of Voice AI. Fuelled by innovation, inclusivity, and a passion for making a global impact through world-leading Speech AI, we're looking for an experienced Principal Machine Learning Engineer to accelerate our efforts towards exceptional speech solutions. 

Our Modelling Team trains diverse models, including large self-supervised ones, supporting Speechmatics towards being the most accurate speech recognition system globally. It also ensures their deployment into production, working with the latest developments in ML, but also with the best engineering practices for software engineering and model serving. 

This is a hands-on, technical leadership role with high ownership.  You will develop and deploy advanced speech systems that power our products as well as co-define the technical vision for ML, drive innovation, and mentor engineering teams. Your work will span the entire codebase.    

What You’ll Do:

• Develop and deploy ML models, translating research into scalable, maintainable code and services 
• Optimise ML models for speed, accuracy, and cost efficiency 
• Evaluate and integrate cutting-edge approaches into our ML stack
• Identify and solve complex ML problems across the organisation
• Define and enforce best practices for code quality, model lifecycle management, etc.
• Mentor engineers and foster a culture of technical excellence and innovation
• Co-define the long-term technical vision 

What We’re Looking For:

• Deep understanding of the modern Machine Learning stack, for example:
  • Knowledge of contemporary transformer architectures (e.g., GQA, KV-caching) and best practices
  • Expertise in distributed training techniques
  • Familiarity with optimisation strategies for model inference (e.g., dynamic batching, flash attention, speculative decoding)
• Proven track record of developing and deploying models at scale
• Expertise in Python, ML frameworks (TensorFlow, PyTorch), and experience with cloud platforms
• Strong familiarity with MLOps principles, CI/CD pipelines, and containerization (Docker, Kubernetes)

  With preferred backgrounds covering some of the following:

• Experience with speech-to-text or text-to-speech 
• Contributions to open-source projects or published research in top-tier conferences

1211 - Director, Data Science - DTA

About WPP Media

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com.

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com

About Choreograph: A Leading WPP Media Brand

Choreograph is WPP’s global data products and technology company. We’re on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation.

We work with agencies and clients to transform the value of data by bringing together technology, data and analytics capabilities. We deliver this through the Open Media Studio, an AI-enabled media and data platform for the next era of advertising.

We’re endlessly curious. Our team of thinkers, builders, creators and problem solvers are over 1,000 strong, across 20 markets around the world.

Role Summary and Impact

The Data Science Director, plays a critical leadership role as part of a broader team in the deployment and development of predictive models for our customers. You will lead and mentor a team, working collaboratively with senior Google Cloud and Google Marketing experts to apply advanced modeling techniques to enhance our customers' media/marketing solutions. As Team Lead you will be responsible for guiding the team in building out industry-relevant predictive models that can be applied to optimize our customers' media investments.

The role focuses on leading the application of analytical solutions based on machine learning & statistical predictive algorithms on top of the Google technology stack and agent development for our customers. We are looking for a Team Lead with significant experience in algorithmic data analysis, proven scientific research skills, and a track record of leading successful data science initiatives.

Skills and Experience

At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values:

• Be Extraordinary by Leading Collectively to Inspire transformational Creativity.
• Create an Open environment by Balancing People and Client Experiences by Cultivating Trust.
• Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise.

This is an excellent opportunity for a Team Lead, to join the Data and Technology Consulting Team. You will be instrumental in strategising how to tackle and take apart large and messy datasets of structured and unstructured data, oversee the building and implementation of models and algorithms, agents and design and run experiments to optimise clients customer insights, analytics and customer experience. The ideal candidate will have a love of getting their hands dirty, while also empowering and developing their team to do the same.

RESPONSIBILITIES:

• Lead the team in the creation, management, and continuous improvement of AI/ML and models and agents used to measure, optimize, and activate business transformation, including creative, media campaigns and broader marketing objectives.
• Drive the development and deployment of industry-relevant strategies and solutions.
• Ensure comprehensive documentation of data science projects, establishing best practices for replicable and scalable analytical processes across clients.
• Guide the team in building out compelling content for presentations to demonstrate the performance and value of statistical and predictive models.
• Oversee the delivery of robust mathematical analysis, ensuring accuracy and strategic relevance.
• Accountable for the team's production of high-standard campaign reports, studies, presentations, and proposals.
• Achieve continuous improvement by proactively assessing Choreograph's working relationships, practices, and methods, and implementing enhancements.
• Lead the establishment and optimization of MLOps processes leveraging the GCP toolset.
• Drive and demonstrate measurable success and impact for clients and the team.

REQUIREMENTS:

• Hands-on experience with building out machine learning models with Python, in a leadership or senior mentorship role.
• Advanced education and background in machine learning, computer science, physics, applied mathematics, or statistics.
• Expert-level hands-on experience in developing complex query structures with SQL and/or NoSQL query languages, and experience guiding others.
• Expert-level hands-on experience working with GCP’s AI Capabilities, including leveraging BigQuery ML, Vertex AI, and other relevant services.
• Extensive hands-on experience with a broad range of machine learning techniques using (TensorFlow, Keras, PyTorch, Scikit-learn, XGBoost, Pandas, NLTK, Spark MLib).
• Deep experience and understanding of deep learning techniques (TensorFlow, Theano, MXNet).
• Proven understanding and experience in software engineering best practices, DevOps, and MLOps, with a track record of implementing or leading these initiatives.
• Solid grounding in applied mathematics, especially optimization and graph theory, and advanced statistics.
• Significant commercial or academic experience in leading the development and deployment of complex ML & AI solutions using Python/R.
• In-depth knowledge of machine learning algorithms and their practical applications.
• Advantageous to have extensive experience in Google Marketing Platform and the use of Ads Data Hub.
• Exceptional capabilities in the areas of data engineering, data modeling, and complex big data analysis, with experience leading teams in these domains.
• Strong business analysis skills and deep understanding of analytics, with the ability to translate complex data into strategic business value.
• Exceptional communication and presentation skills, capable of influencing stakeholders at all levels.
• Passionate about working in an extremely fast-paced, demanding, and fluid environment, with a desire to build and lead a high-performing team and contribute significantly to a growing company.

Life at WPP Media & Benefits

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.  

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.

Please note this is a UK based role and requires individuals to have the right to work in this location

Please read our Privacy Notice (https://www.wppmedia.com/pages/privacy-policy) for more information on how we process the information you provide.

#LI-Promoted

Quant Dev - Systematic Equities Trading

What we do:

Maven’s Systematic Equities team deploys research-driven strategies across global equity markets, powered by some of the most advanced technology available. Our approach to trading is scientific and process-driven, with a strong emphasis on a flexible research environment, providing us with efficient means to rapidly develop, test, and deploy new ideas. We empower our team members and maximise their ability to succeed by offering an environment that is open, collaborative, and supportive. We value creativity and are aggressive to capitalise on opportunities.

The role:

We are looking for an experienced Python Engineer (Platform / ML) to join the mid-frequency-equities desk and help build, maintain, and support all aspects of the trading platform. The role is hands-on and production-facing: you will be expected to react quickly to urgent desk needs, while making pragmatic trade-offs between optimal architecture and fast, reliable delivery.

• Data ingestion and processing pipelines
• Orchestration of all processes involved in the trading platform
• Trading and research platform development and support
• ML model training and inference infrastructure
• Production support for live trading systems
• Monitoring and alerting improvements
• AI tooling integration

Requirements:

• Excellent Python skills, with significant experience designing, developing, testing, and deploying complex and robust production systems
• Familiarity with Linux systems; comfortable debugging distributed/production issues
• Understanding of algorithm design and complexity
• Ability to prioritise effectively in a fast-paced environment whilst keeping longer-term objectives in mind
• Strong ownership mindset: incident handling, end-to-end problem solving, and pragmatic decision making under time pressure
• An interest in trading and finance; experience with systematic trading platforms/frameworks (incl. stat-arb environments) is a strong plus

Ideal experience would include:

• Engineering systems for live trading platforms or similarly demanding real-time environments
• Airflow, Argo, Dagster or equivalent
• Observability/monitoring stacks, dashboards and alert design
• ML infra, high-performance and GPU computing, MLOps 
• Docker, Kubernetes
• CI/CD

Why you should apply:

• A flexible environment where technology is an absolute key to our success
• Opportunity to be highly involved in the decisions that shape every aspect of how we operate
• Friendly, informal and collaborative environment where you’re empowered and supported to achieve your ambitions, learn and develop
• Competitive compensation with substantial impact-based upside

We are a small and nimble team that makes extensive use of CI/CD, AI tooling, and peer code review to ensure quality and maintainability while keeping time-to-market short. You will be able to see the impact of your work immediately and will be in a unique position to directly contribute to trading revenue. 

Miro is the online workspace for innovation, used by 100M+ people to build the next big thing. We are seeking a Research Manager to lead the team defining the brain behind the "Intelligent Canvas."

This is not for building a standard GenAI or Recommendation engine. You will lead a team operating at the intersection of Vision, Language, and Graph Theory, working with a dataset unlike any other in the industry: spatial, unstructured, and deeply human collaboration data. You will bridge the gap between open-ended research (LLMs, Diffusion Models, GNNs) and product impact, empowering teams to dream, design, and build faster.

What You'll Do

• Build and lead a world-class applied research team, hiring and mentoring researchers who excel at the intersection of deep learning theory and production engineering.
• Define the research roadmap to support the "Intelligent Canvas," identifying opportunities to model complex user behaviors—from multi-user collaboration on an infinite canvas, to multi-format AI-powered generation (e.g. slide deck, technical diagram, web app prototypes, etc.), and more.
• Pioneer research on unique spatial datasets. Unlike standard text/image corpuses, you will explore massive multimodal and graph-based datasets, uncovering how teams organize information spatially and collaborate together to solve complex multi-modal problems.
• Drive the "Research-to-Product" velocity. You will create the framework for rapidly testing foundation models (e.g., GPT-4, Llama, Stable Diffusion) and fine-tuning them for specific domain tasks (e.g. prototype generation, diagram generation, mindmap generation).
• Cultivate a culture of scientific rigor. Encourage the team to stay at the cutting edge (NeurIPS, CVPR) while maintaining a relentless focus on shipping features that delight users.
• Partner with Engineering & Product Leadership to translate abstract AI capabilities into intuitive solutions that feel like magic to our users.
• Architect organizational processes for model governance, ensuring rigorous evaluation frameworks, reproducibility, and ethical AI practices.

What We're Looking For

• Proven track record of technical leadership: 2+ years of experience managing high-performing Applied Science or ML Engineering teams in a product-led tech company or top-tier research lab.
• Multimodal & GenAI Depth: You don't just use APIs; you understand the architecture of Transformers, Diffusion models, and Graph Neural Networks (GNNs). You can guide a team through the complexities of fine-tuning and RAG at scale.
• A "Product-First" Researcher: You understand that accuracy metrics (F1, AUC) are proxies, not goals. You prioritize user value and latency constraints in production.
• Curiosity for the "Unsolved": You are excited by the ambiguity of modeling "collaboration." How do you quantify a "good brainstorm"? How do you autocomplete a flowchart?
• Strategic Communication: You can articulate the difference between "hype" and "utility" to executive stakeholders and align research efforts with Miro’s long-term strategy.

Education + Experience

• Option A: PhD in Computer Science, Statistics, Mathematics, or related field + 2+ years of people management experience.
• Option B: Master’s degree or equivalent deep technical experience + 5+ years of industry experience in ML, including 2+ years of people management.

Bonus (Nice-to-Have)

• A portfolio of research contributions, including publications in top-tier conferences (NeurIPS, ICLR, KDD) or impactful technical blog posts.
• Familiarity with the modern MLOps stack and experience guiding teams in building their own research infrastructure.

What's in it for you

We want you to feel supported, connected, and ready to grow. Our global benefits package generally includes equity, a wellbeing benefit, a WFH equipment allowance, and an annual Learning & Development stipend. Join a diverse team where you can do your best work. Full benefits may differ per location. If you would like to learn more about location-specific benefits, please refer to our Global Miro benefits board.

Recruiter: #LI-MH1

Management Consultant: Data Analytics Lead – Managing Principal (Director)

Location: London (Hybrid) | Practice Area: Data & Analytics | Type: Permanent

Lead the strategy. Grow the practice. Redefine data excellence.

The Role
Capco is seeking a visionary Data Analytics Lead at Managing Principal level to spearhead the strategy and growth of our award-winning Data Practice. You’ll lead a team of multidisciplinary practitioners delivering high-impact analytics, AI, and data science projects across the Financial Services sector. This leadership role combines business development, client engagement, capability growth, and proposition innovation.

What You’ll Do

• Shape and drive the growth of Capco’s UK Data Practice, contributing to global data initiatives

• Identify and develop business opportunities, proposals, and data propositions for new and existing clients

• Lead client relationships, guide data strategy discussions, and represent Capco at industry forums

• Inspire, mentor, and grow a high-performing team of data professionals, fostering a collaborative and inclusive culture

• Support delivery of complex, innovative data projects that deliver commercial and customer-focused outcomes

What We’re Looking For

• 8+ years of experience in consulting and currently operating at a senior management or director level

• Track record of building client relationships and securing data-related business opportunities

• Expertise across data domains: data strategy, data governance, data privacy, and analytics delivery

• Strong understanding of data science, AI, MLOps, BI tools, ethics in AI, and analytics operating models

• Proven ability to lead large-scale data transformation initiatives within Financial Services

Bonus Points For

• Experience managing teams in multi-client environments with a focus on collaboration and delivery

• Strong background in programme execution, change management, and stakeholder alignment

• Familiarity with industry-recognised frameworks and tools across AI and data management

• Contributions to thought leadership and innovation in data and analytics

• Demonstrated capability in talent recruitment, development, and performance leadership

Why Join Capco

• Deliver high-impact technology solutions for Tier 1 financial institutions

• Work in a collaborative, flat, and entrepreneurial consulting culture

• Access continuous learning, training, and industry certifications

• Be part of a team shaping the future of digital financial services

• Help shape the future of digital transformation across FS & Energy.

We offer a competitive, people-first benefits package designed to support every aspect of your life:

Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover.
Mental Health: Easy access to CareFirst, Unmind, Aviva consultations, and in-house first aiders.
Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause, and bereavement.
Family Care: 8 complimentary backup care sessions for emergency childcare or elder care.
Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs.
Continuous Learning: Minimum 40 Hours of Training Annually: Take your pick—workshops, certifications, e-learning—your growth, your way. Also, Business Coach assigned from Day One: Get one-on-one guidance to fast-track your goals and accelerate your development.
Healthcare Access: Convenient online GP services.
Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work, and dental insurance.

Inclusion at Capco
We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day.

We have been informed of several recruitment scams targeting the public. We strongly advise you to verify identities before engaging in recruitment related communication. All official Capco communication will be conducted via a Capco recruiter.

#LI-DNI

Applied AI & Analytics - Principal Consultant

Location: London (Hybrid) | Practice Area: Data & Analytics | Type: Permanent

Lead AI-enabled data and analytics programmes that deliver measurable impact across Financial Services. Lead the AI future.

The Role

You’ll lead complex, AI-enabled data and analytics programmes across the financial services sector, combining strategic leadership with deep expertise in applied AI, machine learning and advanced analytics to help clients deliver measurable outcomes at scale.

What You’ll Do

• Scope, prioritise and shape AI and analytics initiatives across top-tier financial institutions
• Lead end-to-end delivery, from problem definition through to delivery, balancing business value, technical feasibility and data readiness
• Own delivery outcomes across AI-enabled initiatives, working hands-on with data scientists, engineers and client stakeholders
• Provide leadership and mentoring to data scientist and AI engineers, supporting capability growth across analytics, AI and ML
• Represent Capco’s Data Practice externally, contributing to AI-focused propositions, partnerships and thought leadership

What We’re Looking For

• Proven experience leading AI-driven data and analytics programmes within consulting or complex enterprise environments
• Strong expertise across applied AI, machine learning, advanced analytics and their integration into modern data platforms to guide delivery, challenge design decisions and ensure solutions scale in production
• Knowledge about  evolving cutting-edge AI technologies - including Agentic AI, GenAI advancements, Knowledge Graphs etc.
• Demonstrated ability to translate AI and analytics capabilities into clear business value for senior stakeholders
• Experience designing, governing and scaling AI solutions within regulated Financial Services environments
• Confidence operating across multiple workstreams while building sustainable AI and analytics capability within teams

Bonus Points For

• Hands-on experience with AI product development, MLOps, model lifecycle management or AI platform engineering
• Knowledge of responsible AI, model risk management, AI governance or ethical AI frameworks
• Experience supporting AI strategy, roadmap definition or AI-enabled operating models
• Comfortable supporting commercial/strategic discussions with internally and with clients

Why Join Capco

• Deliver high-impact technology solutions for Tier 1 financial institutions

• Work in a collaborative, flat, and entrepreneurial consulting culture

• Access continuous learning, training, and industry certifications

• Be part of a team shaping the future of digital financial services

• Help shape the future of digital transformation across FS & Energy.

We offer a competitive, people-first benefits package designed to support every aspect of your life:

Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover.
Mental Health: Easy access to CareFirst, Unmind, Aviva consultations and in-house first aiders.
Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause and bereavement.
Family Care: 8 complimentary backup care sessions for emergency childcare or elder care.
Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs.
Continuous Learning: Minimum 40 Hours of Training Annually: Take your pick - workshops, certifications, e-learning - your growth, your way. Also, Business Coach assigned from Day One: Get one-on-one guidance to fast-track your goals and accelerate your development.
Healthcare Access: Convenient online GP services.
Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work and dental insurance.

Inclusion at Capco
We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day.

We have been informed of several recruitment scams targeting the public. We strongly advise you to verify identities before engaging in recruitment related communication. All official Capco communication will be conducted via a Capco recruiter. #LI-DNI

Data Analytics – Principal Consultant

Location: London (Hybrid) | Practice Area: Data & Analytics | Type: Permanent

Champion innovation. Grow capabilities. Deliver real-world outcomes.

The Role
As a Data Analytics Principal Consultant, you’ll take a central role in supporting the continued growth of Capco’s UK Data Practice. You'll lead complex data and analytics programmes across the financial services sector while mentoring talent, guiding clients and driving innovation across topics such as Cloud, AI and Machine Learning.

What You’ll Do

• Deliver cutting-edge data transformation initiatives across top-tier financial institutions

• Provide leadership and mentoring to data consultants, helping shape career development

• Build strong client relationships and lead data propositions and sales opportunities

• Engage with technical and non-technical stakeholders to champion data literacy and adoption

• Represent Capco’s Data Practice in the market to enhance visibility and develop partnerships

What We’re Looking For

• Minimum 5 years of experience in a consulting or senior management role

• Deep knowledge of data and analytics disciplines such as data quality, governance, BI and ML

• Strong stakeholder engagement skills, from C-suite through to delivery teams

• Experience designing and executing complex data programmes within Financial Services

• Ability to operate across multiple workstreams while developing internal capability

Bonus Points For

• Prior experience in business development or pre-sales within a consultancy environment

• Hands-on familiarity with modern data science, MLOps or AI operationalisation

• Knowledge of data ethics, AI governance or analytics operating models

• Change management or business analysis experience within large transformation programmes

• Confidence in navigating both technical and strategic client discussions

Why Join Capco

• Deliver high-impact technology solutions for Tier 1 financial institutions

• Work in a collaborative, flat, and entrepreneurial consulting culture

• Access continuous learning, training, and industry certifications

• Be part of a team shaping the future of digital financial services

• Help shape the future of digital transformation across FS & Energy.

We offer a competitive, people-first benefits package designed to support every aspect of your life:

Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover.
Mental Health: Easy access to CareFirst, Unmind, Aviva consultations, and in-house first aiders.
Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause and bereavement.
Family Care: 8 complimentary backup care sessions for emergency childcare or elder care.
Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs.
Continuous Learning: Minimum 40 Hours of Training Annually: Take your pick - workshops, certifications, e-learning - your growth, your way. Also, Business Coach assigned from Day One: Get one-on-one guidance to fast-track your goals and accelerate your development.
Healthcare Access: Convenient online GP services.
Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work and dental insurance.

Inclusion at Capco
We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day.

We have been informed of several recruitment scams targeting the public. We strongly advise you to verify identities before engaging in recruitment related communication. All official Capco communication will be conducted via a Capco recruiter. #LI-DNI

Senior Data Engineer - GCP

Location: London (Hybrid) | Practice Area: Technology & Engineering | Type: Permanent

Shape the future of financial services through cloud-first data innovation

The Role
We’re looking for a GCP Senior Data Engineer to join our growing Technology & Engineering team in London. You’ll work with Tier 1 financial institutions on cutting-edge transformation programmes, using your deep expertise in Google Cloud Platform to build robust, scalable data solutions. This role is ideal for engineers who thrive on innovation, take ownership of challenges, and enjoy working in collaborative, agile teams.

What You’ll Do

• Design and build resilient, scalable data pipelines using GCP services such as BigQuery, Dataflow, and Dataproc.

• Collaborate closely with clients to define business requirements and architect fit-for-purpose data solutions.

• Apply engineering best practices across the SDLC, including CI/CD, testing, and version control using Git.

• Support the migration of legacy on-premise systems to cloud-native architectures.

• Champion data governance, security, and compliance, especially in regulated environments.

What We’re Looking For

• Strong hands-on experience with GCP including BigQuery, Pub/Sub, Cloud Composer, and IAM.

• Proven ability in Python, SQL, and PySpark; experience with data lakes, warehousing, and data modelling.

• Demonstrated knowledge of DevOps principles, containerisation, and CI/CD tools such as Jenkins or GitHub Actions.

• A track record of delivering data engineering solutions in agile environments.

• Confident communication skills, able to convey technical concepts to non-technical stakeholders.

Bonus Points For

• Experience with real-time streaming tools like Kafka or Spark Streaming.

• Exposure to MLOps practices and maintaining ML models in production.

• Familiarity with data visualisation tools such as Power BI, Qlik, or Tableau.

• Experience of developing applications on VertixAI is preferable

• Knowledge of both SQL and NoSQL solutions, and the ability to assess trade-offs between ETL and ELT.

Why Join Capco

• Deliver high-impact technology solutions for Tier 1 financial institutions

• Work in a collaborative, flat, and entrepreneurial consulting culture

• Access continuous learning, training, and industry certifications

• Be part of a team shaping the future of digital financial services

• Help shape the future of digital transformation across FS & Energy

We offer a competitive, people-first benefits package designed to support every aspect of your life:

• Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover.

• Mental Health: Easy access to CareFirst, Unmind, Aviva consultations, and in-house first aiders.

• Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause, and bereavement.

• Family Care: 8 complimentary backup care sessions for emergency childcare or elder care.

• Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs.

• Continuous Learning: Minimum 40 Hours of Training Annually: Take your pick—workshops, certifications, e-learning—your growth, your way. Also, Business Coach assigned from Day One: Get one-on-one guidance to fast-track your goals and accelerate your development.

• Healthcare Access: Convenient online GP services.

• Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work, and dental insurance.

Inclusion at Capco
We’re committed to a barrier-free, inclusive recruitment process. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We welcome applicants from all backgrounds. At Capco, we value the difference you make, and the differences that make you. Our #BeYourselfAtWork culture champions diversity, equity and inclusivity, and we bring a collaborative mindset to our partnerships with clients and colleagues. #BeYourselfAtWork is the cornerstone of our success and a value that our employees live and breathe every day.

#LI-DNI

Principal Data Engineer - GCP

Location: London (Hybrid) | Practice Area: Technology & Engineering | Type: Permanent

Shape the future of financial services through cloud-first data innovation

The Role
We’re looking for a Principal GCP Data Engineer to join our growing Technology & Engineering team in London. You’ll work with Tier 1 financial institutions on cutting-edge transformation programmes, using your deep expertise in Google Cloud Platform to build robust, scalable data solutions. This role is ideal for engineers who thrive on innovation, take ownership of challenges, and enjoy working in collaborative, agile teams.

What You’ll Do

• Design and build resilient, scalable data pipelines using GCP services such as BigQuery, Dataflow, and Dataproc.
• Collaborate closely with clients to define business requirements and architect fit-for-purpose data solutions.
• Apply engineering best practices across the SDLC, including CI/CD, testing, and version control using Git.
• Lead in the development of robust, tested, and fault-tolerant data engineering solutions.
• Support and mentor junior engineers, contributing to knowledge sharing across the team.

What We’re Looking For

• Strong hands-on experience with GCP including BigQuery, Pub/Sub, Cloud Composer, and IAM.
• Proven ability in Python, SQL, and PySpark; experience with data lakes, warehousing, and data modelling.
• Demonstrated knowledge of DevOps principles, containerisation, and CI/CD tools such as Jenkins or GitHub Actions.
• A track record of delivering data engineering solutions in agile environments.
• Confident communication skills, able to convey technical concepts to non-technical stakeholders.

Bonus Points For

• Experience with real-time streaming tools like Kafka or Spark Streaming.
• Exposure to MLOps practices and maintaining ML models in production.
• Familiarity with data visualisation tools such as Power BI, Qlik, or Tableau.
• Experience of developing applications on VertixAI is preferable
• Knowledge of both SQL and NoSQL solutions, and the ability to assess trade-offs between ETL and ELT.

Why Join Capco

• Deliver high-impact technology solutions for Tier 1 financial institutions
• Work in a collaborative, flat, and entrepreneurial consulting culture
• Access continuous learning, training, and industry certifications
• Be part of a team shaping the future of digital financial services
• Help shape the future of digital transformation across FS & Energy

We offer a competitive, people-first benefits package designed to support every aspect of your life:

• Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover.
• Mental Health: Easy access to CareFirst, Unmind, Aviva consultations, and in-house first aiders.
• Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause, and bereavement.
• Family Care: 8 complimentary backup care sessions for emergency childcare or elder care.
• Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs.
• Continuous Learning: Minimum 40 Hours of Training Annually: Take your pick—workshops, certifications, e-learning—your growth, your way. Also, Business Coach assigned from Day One: Get one-on-one guidance to fast-track your goals and accelerate your development.
• Healthcare Access: Convenient online GP services.
• Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work, and dental insurance.

Inclusion at Capco
We’re committed to a barrier-free, inclusive recruitment process. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We welcome applicants from all backgrounds. At Capco, we value the difference you make, and the differences that make you. Our #BeYourselfAtWork culture champions diversity, equity and inclusivity, and we bring a collaborative mindset to our partnerships with clients and colleagues. #BeYourselfAtWork is the cornerstone of our success and a value that our employees live and breathe every day.

#LI-DNI

Lead AI Engineer (Principal Consultant)
Location: London (Hybrid) | Practice Area: Technology & Engineering | Type: Permanent

Empower the next frontier of AI with Capco. Shape, build, and deliver future-ready generative systems.

The Role
We’re looking for a Lead AI Engineer (Principal Consultant) to join our Technology Delivery Team. You’ll combine your expertise in AI/ML engineering and software development to build and deploy cutting-edge generative AI and agentic systems across the financial services sector. As a hands-on leader, you’ll architect AI solutions, embed them within enterprise environments, and drive impactful outcomes through advanced engineering, scalable pipelines, and deep cross-functional collaboration.

What You’ll Do

• Architect and develop autonomous AI systems integrating multi-modal LLMs (text, image, audio, video)

• Design agentic workflows enabling AI agents to interact with data sources and APIs using prompt engineering and RAG

• Fine-tune, optimize, and deploy large language and multi-modal models with a focus on performance and latency

• Build scalable MLOps pipelines and full-stack applications to support robust, production-grade AI deployments

• Guide multidisciplinary teams and clients through strategic decisions in AI engineering and GenAI adoption

What We’re Looking For

• Bachelor’s degree or higher in Computer Science, AI, or related STEM fields

• Hands-on experience deploying LLMs and multi-modal models at scale

• Strong engineering background in Python with proven backend and API development skills

• Solid understanding of scalable MLOps, observability, and cloud-native AI deployment

• Excellent communication, problem-solving, and project management skills in agile environments

Bonus Points For

• Experience with agentic frameworks (e.g., LangChain, LlamaIndex)

• Experience in deep learning frameworks and front-end development

• Familiarity with Langfuse, Langsmith, or other LLM observability tools

• Understanding of Model Context Protocol and bias/hallucination mitigation techniques

• Previous success in integrating GenAI solutions into enterprise-scale systems

Why Join Capco

• Deliver high-impact technology solutions for Tier 1 financial institutions

• Work in a collaborative, flat, and entrepreneurial consulting culture

• Access continuous learning, training, and industry certifications

• Be part of a team shaping the future of digital financial services

• Help shape the future of digital transformation across FS & Energy.

Benefits
We offer a competitive, people-first benefits package designed to support every aspect of your life:

• Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover.
• Mental Health: Easy access to CareFirst, Unmind, Aviva consultations, and in-house first aiders.
• Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause, and bereavement.
• Family Care: 8 complimentary backup care sessions for emergency childcare or elder care.
• Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs.
• Continuous Learning: Your growth, your way - minimum 40 Hours of Training Annually. Take your pick; workshops, certifications, e-learning. Also, Business Coach assigned from Day One: Get one-on-one guidance to fast-track your goals and accelerate your development.
• Healthcare Access: Convenient online GP services.
• Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work, and dental insurance.

Inclusion at Capco
We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know - we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day.

#LI-DNI

Senior Data Scientist

Location: London (Hybrid) | Practice Area: Data & Analytics | Type: Permanent

Shape intelligent solutions. Lead with insight. Drive data innovation.

The Role
We are looking for a Senior Data Scientist to join Capco’s growing UK Data Practice. You will play a leading role in designing and implementing cutting-edge data science solutions across financial services. This is an opportunity to build intelligent systems that drive commercial and customer outcomes - while mentoring others and collaborating in a dynamic, multi-disciplinary environment.

What You’ll Do

• Lead the end-to-end delivery of data science solutions including PoCs, MVPs and production deployments

• Develop and prototype ML models to solve complex business challenges using modern techniques and tooling

• Collaborate closely with engineers, domain experts, and business teams to translate requirements into deliverables

• Guide and coach data science pods, supporting skill development and solution design

• Act as a subject matter expert on ML architecture, model calibration and productionisation

What We’re Looking For

• Hands-on experience building and deploying data science solutions in Python and related ML libraries

• Strong background in applied machine learning, model development and data engineering

• Experience with cloud environments (Azure, AWS, GCP) and tools such as Spark, Hive, Redshift

• Demonstrated ability to lead cross-functional teams and mentor junior practitioners

• Ability to communicate complex technical concepts clearly to non-technical audiences

Bonus Points For

• Participation in Kaggle or other data science competitions

• Experience with MLOps practices (CI/CD, model monitoring, DevOps integration)

• Familiarity with advanced NLP frameworks such as spaCy or Transformers

• MSc or PhD in a numerate discipline

• Financial services or banking experience

Why Join Capco

• Deliver high-impact technology solutions for Tier 1 financial institutions

• Work in a collaborative, flat, and entrepreneurial consulting culture

• Access continuous learning, training, and industry certifications

• Be part of a team shaping the future of digital financial services

• Help shape the future of digital transformation across FS & Energy.

We offer a competitive, people-first benefits package designed to support every aspect of your life:

• Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover.
• Mental Health: Easy access to CareFirst, Unmind, Aviva consultations and in-house first aiders.
• Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause and bereavement.
• Family Care: 8 complimentary backup care sessions for emergency childcare or elder care.
• Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs.
• Continuous Learning: Minimum 40 Hours of Training Annually: Take your pick - workshops, certifications, e-learning - your growth, your way. Also, Business Coach assigned from Day One: Get one-on-one guidance to fast-track your goals and accelerate your development.
• Healthcare Access: Convenient online GP services.
• Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work and dental insurance.

Inclusion at Capco
We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day. #LI-DNI

Data Science Manager

Location: London (Hybrid) | Practice Area: Data & Analytics | Type: Permanent

Shape intelligent solutions. Lead with insight. Drive data innovation.

The Role

We’re looking for a Data Science Manager to lead innovative projects that apply data, AI, and machine learning to solve complex challenges across financial services. You’ll guide talented data professionals, collaborate closely with business stakeholders, and drive impactful, scalable solutions that deliver measurable business value.

What You’ll Do

• Lead data science teams to design, develop, and deploy advanced machine learning and AI solutions.
• Drive the adoption of cutting-edge technologies including generative AI, LLMs, and agentic AI frameworks.
• Collaborate with business and technology teams to align technical outcomes with strategic goals.
• Provide thought leadership and best practices across the data science lifecycle, from exploration to deployment.
• Mentor and develop data professionals, fostering a culture of innovation and excellence.

What We’re Looking For

• Proven experience leading the delivery of data science or AI projects from concept to production.
• Strong knowledge of Python and core ML libraries (e.g., spaCy, NumPy, SciPy, Transformers).
• Understanding of big data and cloud technologies (Spark, Hadoop, Azure, AWS, or GCP).
• Deep expertise in MLOps principles, scalable model deployment, and model governance.
• Excellent communication and stakeholder management skills with the ability to translate data insights into business value.

Bonus Points For

• MSc or PhD in a numerate discipline.
• Experience in Banking or Financial Services.
• Exposure to GenAI, LLMs, and intelligent agent workflows.
• Experience with DevOps, CI/CD, and productionising ML systems.
• A passion for mentoring and developing early-career data talent.

Why Join Capco

• Deliver innovative, high-impact data solutions for Tier 1 financial institutions.
• Work in a collaborative, entrepreneurial consulting environment.
• Access continuous learning, training, and industry certifications.
• Join a growing global Data Practice of 800+ experts driving transformation.
• Be part of a culture where individuality, creativity, and collaboration are celebrated.

We offer a competitive, people-first benefits package designed to support every aspect of your life:

• Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover.
• Mental Health: Easy access to CareFirst, Unmind, Aviva consultations, and in-house first aiders.
• Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause, and bereavement.
• Family Care: 8 complimentary backup care sessions for emergency childcare or elder care.
• Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs.
• Continuous Learning: Minimum 40 hours of training annually-choose workshops, certifications, or e-learning-your growth, your way. Business Coach assigned from Day One for one-on-one guidance.
• Healthcare Access: Convenient online GP services.
• Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work, and dental insurance.

Inclusion at Capco

We’re committed to a barrier-free, inclusive recruitment process. If you need any adjustments at any stage, just let us know -we’ll be happy to help. We welcome applicants from all backgrounds. At Capco, we value the difference you make, and the differences that make you. Our #BeYourselfAtWork culture champions diversity, equity, and inclusion, and we bring a collaborative mindset to everything we do #LI-DNI

We are currently looking for a Senior Data Engineer to join us remotely in the UK as we plan to set up a hub in the UK in the following 6-12 months to enable our GTM strategy. You will work with our EMEA and US customers to help them solve their data engineering, ML, ML Ops, and cloud migration puzzles.

"As a Data Engineer at DATAPAO, you will have the unique opportunity to push the boundaries of technology and lead the way in how data transforms the world. We work with customers who want to innovate and change their industries. So it never gets boring! Sorting out a complex technical puzzle, setting up a new data architecture from scratch, or guiding our customers through adopting the latest technologies is our routine here. Hence, we'd expect you to be more than just a (data) engineer. We'd expect you to breathe and live data, to thrive for knowledge and excellence, and to be keen to build something enduring and impactful for our customers. We'd expect you to be a (data) Paoneer!"  (Máté Gulyás, CEO)

What will you do?

As a Senior Data Engineer, you are expected to deliver (across industries) on some of our most complex projects - individually or by leading small delivery teams. Although we work for the biggest multinational companies where years-long behemoth projects are the norm, our projects are fast-paced, typically 2 to 4 months long. Most are delivered using Apache Spark/Databricks on AWS/Azure and require you to directly manage the customer relationship alone or in collaboration with a Project Manager. Additionally, at this seniority level, we expect you to compound your impact across the team and the organization - by supporting our pre-sales process, mentoring more junior engineers, and contributing to hiring best-in-class data talent.

What does it take to fit the bill?

Technical Expertise