This senior role focuses on strengthening the quality engineering foundation for our SDK by developing robust automation, scalable CI/CD systems, and effective test strategies. You will work closely with cross-functional partners to enhance test coverage, improve workflows, and ensure reliable delivery across multiple platforms. The role requires strong technical depth, collaborative working, and the ability to drive meaningful impact quickly.

What you’ll be doing

• Designing, implementing, and maintaining CI/CD pipelines to support build, test, and release workflows.
• Developing automation and tooling in Python to streamline test orchestration and system validation.
• Creating and running automated tests across unit, integration, and system layers.
• Debugging and diagnosing issues across build, test, and deployment environments.
• Supporting Linux and Windows development environments and contributing to cross-platform scripting.
• Applying modern test frameworks and quality metrics to improve test strategy and reporting.
• Collaborating closely with multiple SDK teams to align on shared initiatives.
• Participating in rotational assignments to deepen domain expertise and broaden cross-project knowledge.
• Coordinating with teams across London, Bristol, and Dublin, including occasional travel as needed.
• Mentoring peers, sharing best practices, and influencing quality engineering approaches.

What we are looking for

• Experience building and maintaining CI/CD pipelines (Jenkins/Groovy or equivalent).
• Strong Python 3 skills for automation, tooling, and test orchestration.
• Experience developing and executing automated tests at multiple levels.
• Fluency with Linux and Windows development environments.
• Proficiency with scripting languages such as python, bash, or PowerShell.
• Ability to diagnose and resolve issues across complex build and test systems.
• Familiarity with test frameworks such as pytest, GTest, or similar.
• Understanding of software quality metrics, reporting, and test strategy.
• Experience or awareness in one or more additional areas: C/C++, CMake, C#, Rust, .NET, Docker, Kubernetes, VM orchestration, graphics APIs, AIML/MLOps, or desktop app testing.
• Strong communication and collaboration skills, with the ability to work effectively across distributed teams and represent quality engineering perspectives.

PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the country they reside in.

About the Program

The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers.

What You'll Do

• ML Projects: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Help models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and advising on GPU optimization, scaling, and trade-offs.
• HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains.
• Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., SciPredict, PropensityBench, Professional Reasoning Benchmark).

Who Should Apply

• Education: PhD or postdoctoral degree in Computer Science, Computer Engineering, or a related field.
• Professional Background: 1-3+ years of experience as a Machine Learning Engineer or Data Scientist.
• Skills: Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow). Experience with cloud infrastructure (AWS) and MLOps tools (Docker, Langchain) is a plus.
• Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration.

Why Join the HFC?

• Professional Development: High-impact experts expand their influence through review projects, advisory roles, and research, while deepening their AI expertise, strengthening analytical and problem-solving skills, and engaging with pioneering AI applications in science and technology.
• Join a Top-Tier Network: Collaborate with a global network of engineers and experts to advance responsible AI through impactful, flexible research and training. 80% of our members come from leading institutions.
• Flexible Schedule: Set your own schedule, with flexible 10–40 hour weeks that fit around your life and other commitments.
• Competitive Pay: Project pay rates vary across platforms and are depending on a number of factors, including but not limited to; projects, scope, skillset, and location. 

Application Process

1. Apply: We review applications on a rolling basis.
2. Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI.
3. Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship.

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

The role

We are seeking a highly skilled and customer-focused professional to join our team as a Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines.

You’re welcome to work from the United Kingdom.

Your responsibilities will include: 

• Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices.
• Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers.
• Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI.
• Act as a single point of expertise of customer scenarios for product, technical support, marketing teams.
• Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)

We expect you to have: 

• 5+ years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing
• Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python
• Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL)
• Excellent communication skills
• Customer-centric mindset

It will be an added bonus if you have: 

• Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow)
• Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch)
• Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google) 

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.

The role

We are seeking a customer-obsessed Solutions Architect to lead technical engagement with Nebius customers across Europe. This role is focused on presales excellence, strong technical storytelling, and driving adoption of Nebius AI Cloud across a wide range of industry segments.

As a Solutions Architect, you will act as a trusted technical partner to customers, helping them understand, evaluate, and adopt Nebius for their AI/ML and high-performance computing workloads. You will combine deep technical expertise with strong communication skills to clearly articulate Nebius’ value proposition and differentiate our platform in a competitive market.

You’re welcome to work remotely from Europe.

Your responsibilities will include:

• Own end-to-end technical presales engagements, from discovery through solution design, PoC execution, and production readiness
• Serve as a trusted technical advisor to customer stakeholders, including CTOs, Heads of AI/ML, and platform engineering teams
• Deliver compelling technical presentations, demos, and workshops that clearly communicate the value of Nebius across different customer segments
• Execute demos and PoCs to demonstrate performance, scalability, and cost efficiency of Nebius solutions
• Translate customer requirements into scalable, production-ready architectures and best practices
• Collaborate closely with Sales, Product, and Engineering to align customer needs with Nebius capabilities and roadmap
• Act as a technical advocate for customers internally, ensuring feedback is incorporated into product and go-to-market strategy
• Support regional go-to-market efforts, including events, meetups, webinars, and technical content creation
• Contribute to building repeatable technical playbooks and assets for the European market

We expect you to have:

• 2–5+ years of experience in technical roles such as Solutions Architect, Cloud Architect, Sales Engineer, or similar, with strong customer-facing exposure
• Proven experience in presales or customer-facing technical roles, including discovery, solution design, and PoC execution
• Strong ability to deliver technical pitches and clearly explain complex infrastructure and AI/ML concepts to both technical and business audiences
• Experience positioning cloud or infrastructure solutions and articulating value propositions in competitive environments
• Solid understanding of ML/AI workloads, including training and inference, and the underlying infrastructure requirements
• Experience with cloud platforms, Kubernetes, and distributed systems
• Hands-on experience with Infrastructure as Code (e.g., Terraform) and scripting/programming (Python preferred)
• Strong communication and storytelling skills, with the ability to adapt messaging across different customer segments
• Deep understanding of the European market, including customer expectations, buying behaviors, and local ecosystem
• Fluency in English plus another language preferred (both written and spoken), with the ability to engage confidently with local customers and stakeholders
• A highly customer-centric mindset, with the ability to balance technical depth and business value

It will be an added bonus if you have:

• Experience with GPU-accelerated workloads and AI infrastructure (NVIDIA ecosystem, CUDA, etc.)
• Hands-on experience with MLOps tools and frameworks (Kubeflow, MLflow, etc.)
• Familiarity with HPC environments and schedulers (e.g., Slurm)
• Experience contributing to regional go-to-market or developer/community initiatives

The role

We seek an experienced Specialist Solutions Architect to support AI-focused customers leveraging Nebius services. In this role, you will be a trusted advisor, collaborating with clients to design scalable AI solutions, resolve technical challenges and manage large-scale AI deployments involving hundreds to thousands of GPUs.

You’re welcome to work on-site in Amsterdam or remotely from any other EU country.

Your responsibilities will include:

• Designing customer-centric solutions that maximize business value and align with strategic goals.
• Building and maintaining long-term relationships to foster trust and ensure customer satisfaction.
• Delivering technical presentations, producing whitepapers, creating manuals and hosting webinars for audiences with varying technical expertise.
• Collaborating with engineering and product teams to effectively prioritize and relay customer feedback.

We expect you to have:

• 3+ years of experience with cloud technologies in MLOps engineering, Machine Learning engineering or similar roles.
• Strong understanding of ML ecosystems, including models, use cases and tooling.
• Proven experience in setting up and optimizing distributed training pipelines across multi-node and multi-GPU environments.
• Hands-on knowledge of frameworks like PyTorch or JAX.
• Excellent verbal and written communication skills.

It will be an added bonus if you have:

• Expertise in deploying inference infrastructure for production workloads.
• Ability to transition ML pipelines from POC to scalable production systems.

Preferred tooling:

• Programming Languages – Python, Go, Java, C++
• Orchestration – Kubernetes (K8s), Slurm
• DevOps Tools – Git, Docker, Helm
• Infrastructure as Code (IaC) – Terraform
• ML Frameworks and Libraries – PyTorch, TensorFlow, JAX, HuggingFace, Scikit-learn

Role & Team

We’re looking for a Director of Platform & Infrastructure to own and evolve our core engineering foundations. Reporting to our VP of Product Engineering, this role will lead SRE, MLOps, and Platform teams with a mandate to create leverage across the entire organization.

As a scaling startup, we’re evolving from early-stage infrastructure to a more mature, reliable platform that can support rapid product development and growing customer demand. This role is critical in helping us make that transition — building systems, standards, and teams that enable speed today while laying the foundation for long-term scale.

Partnering closely with product, data, and application engineering teams, you will set the technical vision, define best practices, and ensure our infrastructure enables teams to move fast with confidence.

This is a highly cross-functional leadership role for someone who combines deep technical judgment with a systems mindset, strong people leadership, and a passion for building platforms that empower others.

Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)

What You'll Do 

• Own the platform strategy across Platform, MLOps, and SRE, aligning it with company and product goals
• Grow senior ICs (and eventually manages) across multiple teams, fostering strong technical leadership and healthy team cultures
• Define and evolve our platform vision, including developer experience, internal tooling, CI/CD, infrastructure, observability, and reliability standards
• Oversee MLOps systems that support model development, training, deployment, monitoring, and governance in production
• Partner cross-functionally with Product, ML, Data, Security, and Compliance to ensure the platform meets current and future needs
• Balance speed and stability, making thoughtful tradeoffs between innovation, cost, reliability, and operational excellence
• Set metrics and accountability for platform performance, reliability, and developer productivity

Skills & Experience

• 10+ years experience leading platform, infrastructure, or reliability teams in a scaling startup environment, including navigating ambiguity, rapid growth, and the transition from early-stage systems to more mature, repeatable platforms
• Strong understanding of cloud-native infrastructure (GCP strongly preferred), Kubernetes, CI/CD, and modern DevOps practices
• Experience supporting machine learning systems in production, including model deployment, monitoring, and lifecycle management
• A track record of building reliable, scalable systems used by fast-moving product teams
• Excellent people leadership skills — you know how to coach managers, grow talent, and build inclusive, high-performing teams
• Strong communication skills and the ability to influence across org boundaries
• Experience in data- or ML-heavy products

Nice To Have

• Experience with geospatial data, image processing or mapping technology 

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer

• Competitive, location-specific compensation and benefits.  
• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets 
• A company culture that genuinely embodies each of our core values
• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis

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

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.

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

About the Role

We’re hiring an AI Solutions Architect to lead the future of IT systems and automation at Fortis. This senior-level role focuses on improving how our internal tech works — using AI, automation, and innovative design to make everything more secure, scalable, and efficient.

You’ll lead the design of our IT tools and platforms, ensuring they’re modern, user-friendly, and powered by cutting-edge AI like LLMs (think ChatGPT, Gemini, and similar tools). This role reports to the Director of IT. It works closely with Security, Legal, Engineering, and other departments to ensure our IT systems are robust, safe, compliant, and built to scale.

This isn’t just an execution or admin role — it’s a leadership position for someone who can research, propose, and help drive future-focused IT strategies across the business.

What You'll Achieve

• Define and implement scalable, secure, AI-driven IT architectures aligned with business needs.
• Research, propose, and implement AI/LLM-based automation for IT processes, support systems, and knowledge management.
• Lead AI initiatives and strategy sessions, chairing technology trend discussions and quarterly IT innovation reviews.
• Architect and deploy cloud-native, automation-first IT systems — focused on resilience, performance, and zero-touch management.
• Implement AI-powered IT service desk solutions, compliance monitoring, incident response, and proactive issue resolution.
• Guide IT Operations in optimizing hardware lifecycle, SaaS platforms, and IT asset tracking through AI/automation-driven efficiency.
• Collaborate closely with Security and Legal teams to align AI and IT architecture with compliance, risk management, and privacy standards.
• Drive tool rationalization and consolidation projects using AI analytics to inform more intelligent decision-making.
• Partner with engineering, AI/ML teams, and vendors to integrate IT systems into our broader AI development ecosystem.

What You’ll Need to Be Successful

• Solid experience in IT engineering, IT architecture and cloud-native systems — with a recent, strong focus on AI, automation, and LLMs.
• Experience with AI technologies like large language models (LLMs), MLOps tools, and generative AI platforms (e.g., ChatGPT/OpenAI, Gemini AI, Notion AI). You’ve used these tools to help build or improve systems, not just test them.
• Practical experience building, integrating, or experimenting with AI models, LLMs, and AI-driven workflows.
• Working knowledge of enterprise IT environments, including Google Workspace, Okta, JAMF, Intune, Zoom, Slack, and Cisco Meraki, plus an understanding of cloud infrastructure (AWS, GCP, or Azure).
• Exceptional skills in technical documentation, architecture diagramming, and project planning and execution, plus an understanding of  GDPR, NIST, and SOC 2.
• Ability to explain complex technology and AI clearly and simply to all audiences. Skilled at leading conversations that shape the right technology direction, drive innovation, and bring new ideas to life. 
• Confident in leading executive meetings, managing AI committees, and guiding leadership teams toward smart, forward-thinking technology decisions.
• Game/software development experience strongly preferred where LLMs or automation were part of the tech stack, showcasing creativity, speed, and next-gen thinking.

About the Role

We’re hiring an AI Solutions Architect to lead the future of IT systems and automation at Fortis. This senior-level role focuses on improving how our internal tech works — using AI, automation, and innovative design to make everything more secure, scalable, and efficient.

You’ll lead the design of our IT tools and platforms, ensuring they’re modern, user-friendly, and powered by cutting-edge AI like LLMs (think ChatGPT, Gemini, and similar tools). This role reports to the Director of IT. It works closely with Security, Legal, Engineering, and other departments to ensure our IT systems are robust, safe, compliant, and built to scale.

This isn’t just an execution or admin role — it’s a leadership position for someone who can research, propose, and help drive future-focused IT strategies across the business.

What You'll Achieve

• Define and implement scalable, secure, AI-driven IT architectures aligned with business needs.
• Research, propose, and implement AI/LLM-based automation for IT processes, support systems, and knowledge management.
• Lead AI initiatives and strategy sessions, chairing technology trend discussions and quarterly IT innovation reviews.
• Architect and deploy cloud-native, automation-first IT systems — focused on resilience, performance, and zero-touch management.
• Implement AI-powered IT service desk solutions, compliance monitoring, incident response, and proactive issue resolution.
• Guide IT Operations in optimizing hardware lifecycle, SaaS platforms, and IT asset tracking through AI/automation-driven efficiency.
• Collaborate closely with Security and Legal teams to align AI and IT architecture with compliance, risk management, and privacy standards.
• Drive tool rationalization and consolidation projects using AI analytics to inform more intelligent decision-making.
• Partner with engineering, AI/ML teams, and vendors to integrate IT systems into our broader AI development ecosystem.

What You’ll Need to Be Successful

• Solid experience in IT engineering, IT architecture and cloud-native systems — with a recent, strong focus on AI, automation, and LLMs.
• Experience with AI technologies like large language models (LLMs), MLOps tools, and generative AI platforms (e.g., ChatGPT/OpenAI, Gemini AI, Notion AI). You’ve used these tools to help build or improve systems, not just test them.
• Practical experience building, integrating, or experimenting with AI models, LLMs, and AI-driven workflows.
• Working knowledge of enterprise IT environments, including Google Workspace, Okta, JAMF, Intune, Zoom, Slack, and Cisco Meraki, plus an understanding of cloud infrastructure (AWS, GCP, or Azure).
• Exceptional skills in technical documentation, architecture diagramming, and project planning and execution, plus an understanding of  GDPR, NIST, and SOC 2.
• Ability to explain complex technology and AI clearly and simply to all audiences. Skilled at leading conversations that shape the right technology direction, drive innovation, and bring new ideas to life. 
• Confident in leading executive meetings, managing AI committees, and guiding leadership teams toward smart, forward-thinking technology decisions.
• Game/software development experience strongly preferred where LLMs or automation were part of the tech stack, showcasing creativity, speed, and next-gen thinking.

About the Role

We’re hiring an AI Solutions Architect to lead the future of IT systems and automation at Fortis. This senior-level role focuses on improving how our internal tech works — using AI, automation, and innovative design to make everything more secure, scalable, and efficient.

You’ll lead the design of our IT tools and platforms, ensuring they’re modern, user-friendly, and powered by cutting-edge AI like LLMs (think ChatGPT, Gemini, and similar tools). This role reports to the Director of IT. It works closely with Security, Legal, Engineering, and other departments to ensure our IT systems are robust, safe, compliant, and built to scale.

This isn’t just an execution or admin role — it’s a leadership position for someone who can research, propose, and help drive future-focused IT strategies across the business.

What You'll Achieve

• Define and implement scalable, secure, AI-driven IT architectures aligned with business needs.
• Research, propose, and implement AI/LLM-based automation for IT processes, support systems, and knowledge management.
• Lead AI initiatives and strategy sessions, chairing technology trend discussions and quarterly IT innovation reviews.
• Architect and deploy cloud-native, automation-first IT systems — focused on resilience, performance, and zero-touch management.
• Implement AI-powered IT service desk solutions, compliance monitoring, incident response, and proactive issue resolution.
• Guide IT Operations in optimizing hardware lifecycle, SaaS platforms, and IT asset tracking through AI/automation-driven efficiency.
• Collaborate closely with Security and Legal teams to align AI and IT architecture with compliance, risk management, and privacy standards.
• Drive tool rationalization and consolidation projects using AI analytics to inform more intelligent decision-making.
• Partner with engineering, AI/ML teams, and vendors to integrate IT systems into our broader AI development ecosystem.

What You’ll Need to Be Successful

• Solid experience in IT engineering, IT architecture and cloud-native systems — with a recent, strong focus on AI, automation, and LLMs.
• Experience with AI technologies like large language models (LLMs), MLOps tools, and generative AI platforms (e.g., ChatGPT/OpenAI, Gemini AI, Notion AI). You’ve used these tools to help build or improve systems, not just test them.
• Practical experience building, integrating, or experimenting with AI models, LLMs, and AI-driven workflows.
• Working knowledge of enterprise IT environments, including Google Workspace, Okta, JAMF, Intune, Zoom, Slack, and Cisco Meraki, plus an understanding of cloud infrastructure (AWS, GCP, or Azure).
• Exceptional skills in technical documentation, architecture diagramming, and project planning and execution, plus an understanding of  GDPR, NIST, and SOC 2.
• Ability to explain complex technology and AI clearly and simply to all audiences. Skilled at leading conversations that shape the right technology direction, drive innovation, and bring new ideas to life. 
• Confident in leading executive meetings, managing AI committees, and guiding leadership teams toward smart, forward-thinking technology decisions.
• Game/software development experience strongly preferred where LLMs or automation were part of the tech stack, showcasing creativity, speed, and next-gen thinking.

About the Role

We’re hiring an AI Solutions Architect to lead the future of IT systems and automation at Fortis. This senior-level role focuses on improving how our internal tech works — using AI, automation, and innovative design to make everything more secure, scalable, and efficient.

You’ll lead the design of our IT tools and platforms, ensuring they’re modern, user-friendly, and powered by cutting-edge AI like LLMs (think ChatGPT, Gemini, and similar tools). This role reports to the Director of IT. It works closely with Security, Legal, Engineering, and other departments to ensure our IT systems are robust, safe, compliant, and built to scale.

This isn’t just an execution or admin role — it’s a leadership position for someone who can research, propose, and help drive future-focused IT strategies across the business.

What You'll Achieve

• Define and implement scalable, secure, AI-driven IT architectures aligned with business needs.
• Research, propose, and implement AI/LLM-based automation for IT processes, support systems, and knowledge management.
• Lead AI initiatives and strategy sessions, chairing technology trend discussions and quarterly IT innovation reviews.
• Architect and deploy cloud-native, automation-first IT systems — focused on resilience, performance, and zero-touch management.
• Implement AI-powered IT service desk solutions, compliance monitoring, incident response, and proactive issue resolution.
• Guide IT Operations in optimizing hardware lifecycle, SaaS platforms, and IT asset tracking through AI/automation-driven efficiency.
• Collaborate closely with Security and Legal teams to align AI and IT architecture with compliance, risk management, and privacy standards.
• Drive tool rationalization and consolidation projects using AI analytics to inform more intelligent decision-making.
• Partner with engineering, AI/ML teams, and vendors to integrate IT systems into our broader AI development ecosystem.

What You’ll Need to Be Successful

• Solid experience in IT engineering, IT architecture and cloud-native systems — with a recent, strong focus on AI, automation, and LLMs.
• Experience with AI technologies like large language models (LLMs), MLOps tools, and generative AI platforms (e.g., ChatGPT/OpenAI, Gemini AI, Notion AI). You’ve used these tools to help build or improve systems, not just test them.
• Practical experience building, integrating, or experimenting with AI models, LLMs, and AI-driven workflows.
• Working knowledge of enterprise IT environments, including Google Workspace, Okta, JAMF, Intune, Zoom, Slack, and Cisco Meraki, plus an understanding of cloud infrastructure (AWS, GCP, or Azure).
• Exceptional skills in technical documentation, architecture diagramming, and project planning and execution, plus an understanding of  GDPR, NIST, and SOC 2.
• Ability to explain complex technology and AI clearly and simply to all audiences. Skilled at leading conversations that shape the right technology direction, drive innovation, and bring new ideas to life. 
• Confident in leading executive meetings, managing AI committees, and guiding leadership teams toward smart, forward-thinking technology decisions.
• Game/software development experience strongly preferred where LLMs or automation were part of the tech stack, showcasing creativity, speed, and next-gen thinking.

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

#LI-REMOTE #LI-AM1

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

#LI-REMOTE #LI-AM1

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

#LI-REMOTE #LI-AM1

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

#LI-REMOTE #LI-AM1

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

#LI-REMOTE #LI-AM1

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

#LI-REMOTE #LI-AM1

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices, including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

#LI-AM1

Location: Remote with expected travel into Paddington 2 days per week.

How You'll Make an Impact:

As a Machine Learning Ops Engineer, you will play a key role in building and implementing features that empower lodging customers to make data-driven pricing decisions. Some of these features will use simple heuristic data, while others will leverage advanced machine learning techniques to optimize revenue strategies.

You’ll work closely with product and engineering teams to identify opportunities for improvement, develop innovative solutions, and drive revenue growth for the hotels that rely on our platform. Your impact will be focused on ensuring the reliability, scalability, and high quality of our ML systems from development to production. You’ll be instrumental in establishing robust MLOps practices and rigorous testing processes across the entire ML lifecycle. From structuring data pipelines to implementing and validating ML models, you’ll own the end-to-end development of our revenue management application—ensuring hotels have the reliable, accurate insights they need to maximize their success.

Our Machine Learning Team:

Our machine learning team is energized by the unique challenge of revolutionizing guest experiences through AI-driven insights, transforming traditional hospitality with cutting-edge predictive algorithms. 

We thrive on collaborative innovation, where data scientists, engineers, and product experts seamlessly blend their expertise to prototype bold ideas and directly impact operational efficiency. 

People who are passionate about continuous learning, unafraid to challenge conventions, and excited by the intersection of hospitality and deep technical prowess will find their home among our forward-thinking team.

What You Bring to the Team:

1. Develop and implement end-to-end machine learning features that enable customers to optimize their revenue strategies, with a strong emphasis on production readiness and system reliability.
2. Establish and maintain robust MLOps practices, including CI/CD for model training, testing, deployment, and monitoring.
3. Design, build, and maintain highly reliable and well-tested data and ML pipelines to extract, transform, and structure large datasets for ML applications.
4. Expertise in using Apache Airflow (or similar orchestration tools like Prefect/Dagster) to define, schedule, and monitor complex data and ML workflows (DAGs).
5. Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing for both code and data/model performance.
6. Design, train, and rigorously test machine learning models where needed to improve pricing optimization, focusing on statistical validation and production stability.
7. Implement model performance monitoring (e.g., drift detection, data quality checks) to ensure deployed models maintain accuracy and relevance over time.
8. Collaborate cross-functionally with product, engineering, and data science teams to define SLIs/SLOs for ML services and improve system performance, stability, and usability.
9. Conduct structured A/B testing and experimentation to validate model effectiveness and continuously improve performance, documenting results and sharing technical insights.

What Sets You Up for Success:

1. Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2. 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
3. Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness, performance testing).
4. Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
5. Strong Python programming skills and adherence to software engineering best practices (e.g., clean code, version control, code reviews).
6. Expert-level SQL skills and experience working with large datasets for analysis and modeling.
7. Strong problem-solving skills with the ability to apply creative, data-driven solutions to complex business challenges.
8. Excellent communication and collaboration skills, with experience working cross-functionally with product and engineering teams.

Bonus Skills to Stand Out (Optional):

1. Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
2. Experience with data quality monitoring tools and frameworks.
3. Master’s or PhD in Computer Science, Data Science, or a related field. Relevant certifications (AWS, MLFlow, or other data science/ML certifications).

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

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.

A resident of JetBrains' startup incubator, Spectrum enjoys startup speed and autonomy, and is backed by 25 years of developer tooling expertise. We are looking for a Senior AI/ML Engineer to build and evolve the ML-powered systems at the heart of our product.

Your responsibilities will include:

• Designing and building the ML/LLM solution for data ingestion, knowledge extraction and retrieval, and subsequent reasoning.
• Creating datasets, metrics, and pipelines that drive measurable improvements across the system.
• Architecting and improving AI agents, which will involve prompt engineering, model selection, and inference optimization.
• Contributing to our MLOps practices, including orchestration, observability, and experiment tracking.

We expect you to have:

• At least four years of experience building ML/AI systems in production environments, with hands-on LLM experience.
• 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 LangGraph, Pydantic AI, or an equivalent.
• Retrieval-augmented generation (RAG) patterns and vector databases.
• 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 also have:

• Experience with ontologies, knowledge graphs, or graph-based reasoning.
• Experience in early-stage startups – you enjoy the zero-to-one phase.
• 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.
• A motivated team that moves fast, with short feedback loops, rapid prototyping, and lots of ownership.
• Opportunities to publish research at top venues in collaboration with JetBrains Research.

#LI-DNI

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…

We are looking for a Senior Data Scientist to join our Product Engineering team in Helsinki, Dublin, or the UK. 

If you are a naturally curious problem-solver who thrives on discovering innovative ways to extract value from data, this is your chance to lead high-impact initiatives for a fast-growing SaaS powerhouse

In this role, you will… 

• Solving the "Unsolvable": Dive into massive datasets to architect and implement robust, data-driven solutions that solve high-stakes business problems for our customers.
• Product-Embedded Innovation: Focus on building and embedding insights directly into the Supermetrics product suite, moving beyond theory into live, functional features.
• The Scale-Up Mindset: Thrive in a high-velocity environment where you are expected to pioneer new solutions, remain creative, and lead with a relentless "product-first" focus.
• Fueling the AI Engine: Leverage Supermetrics’ one-of-a-kind dataset to build market-differentiated products. If data is the fuel for AI, you’ll be sitting on one of the best "refineries" in the industry.
• High-Leverage Impact: Utilize our unique data access to create solutions that simply can’t be built anywhere else, giving you the platform to make a massive, visible impact on the industry

Your day-to-day work and responsibilities include…

• Identify opportunities to use advanced data science techniques leveraging a wide variety of MarTech data to solve problems and provide new insights to our customers.
• Develop and deploy AI/ML solutions, creating new products and value for our customers.
• Transform data science prototypes into scalable, production-ready, data-driven products in partnership with our infrastructure/engineering teams.
• Embed AI-powered features and automation tools in data science applications to improve velocity, product quality and customer experience as needed.
• Communicate the impact and outcomes of data science initiatives to stakeholders across the organization.
• Stay current with AI/ML advancements and continually seek for new ideas or paradigms that will add value to our customers.

This position is for you if you have…

• An advanced degree in a STEM-related field such as Mathematics, Statistics, Computer Science, Engineering, or a related field, or equivalent work experience.
• 5+ years of experience in Data Science or ML and AI with real-world data within a product development and/or research setting.
• Expertise in statistical analysis, ML modeling, experimentation, and optimization.
• Hands-on experience working with LLMs and AI agents, including fine-tuning, retrieval-augmented generation (RAG), and deploying models to enhance product features.
• A proactive mindset, a continual pursuit of new ideas and data sources, and the ability to systematically tackle ambiguous problems with a data-driven, hypothesis-based approach.
• Proficiency in Python and SQL, with experience using libraries such as Pandas, NumPy, Scikit-learn, and deep learning frameworks like TensorFlow or PyTorch.
• Experience working with Agent frameworks (e.g. google adk, LangChain) and AI agent evaluation
• Expert-level experience building and deploying data science products using cloud platforms (e.g., AWS, GCP) and MLOps tools.
• Strong project management experience and ability to work with a diverse, distributed, and talented group of people.
• Excellent written and verbal communication skills to explain technical concepts to non-technical stakeholders.
• Domain knowledge of large-scale, data-driven SaaS applications.

We also appreciate…

• Experience with MarTech advanced analytics techniques and use cases (i.e. propensity modelling, Media Mix Modelling, personalisation/customer segmentation).
• Experience in the end-to-end development of AI products.

Benefits we offer…

• Competitive compensation package, including equity
• Great work equipment, and home office allowance for those working in our fully remote locations
• Health care benefit and leisure time insurance
• Annual 1000 euros of personal learning budget
• Sports and wellbeing allowance

Benefits may vary depending on location. 

Hear why our team likes it here at supermetrics.com/careers/life-at-supermetrics.

Get to know our Engineering team at supermetrics.com/careers/engineering

#LI-Remote / #LI-Hybrid #LI-FullTime

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

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 Berlin office or full remote from any part of Germany.

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

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.

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

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

Eligible locations:

• USA
• Canada
• UK
• Portugal
• Spain
• France
• Italy
• Germany
• Netherlands
• Poland
• Czech republic
• Israel
• UAE

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

Eligible locations:

• USA
• Canada
• UK
• Portugal
• Spain
• France
• Italy
• Germany
• Netherlands
• Poland
• Czech republic
• Israel
• UAE

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

Eligible locations:

• USA
• Canada
• UK
• Portugal
• Spain
• France
• Italy
• Germany
• Netherlands
• Poland
• Czech republic
• Israel
• UAE

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

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

About us

At Ada, we envision a world where everyone gets the healthcare they need. Yet, millions remain undiagnosed and untreated due to the complexity of identifying rare and underrecognized conditions, even when effective treatments exist

We’re changing that. Powered by leading AI and built by a team of physicians and clinical scientists, Ada helps people get answers faster, identifying those at risk and guiding them to the right care. Every successful journey makes us smarter and able to help more people.

If you’re passionate about transforming healthcare and ensuring no one goes undiagnosed, join us and be part of what’s next.

About the role

As our Senior AI Engineer, you will play a key role in advancing the development, validation, and supporting tooling of our patented hybrid AI architecture. Our core technology combines Probabilistic Graphical Models (PGMs) with Generative AI to deliver explainable, transparent, and clinically robust medical reasoning. In this role, you will help shape how these components evolve and scale, ensuring they meet high standards for performance, reliability, and regulatory readiness.

Reporting to our Director of AI, you will operate at the intersection of medical intelligence and software engineering—translating complex requirements into sophisticated technical solutions. You’ll collaborate closely with AI researchers, engineers, and medical experts, contributing to both the strategic direction of the platform and the hands-on implementation of production-grade systems.

This is a remote role, open to candidates based in the UK or Germany.

What you’ll do

• System Evolution: Refine and scale our patented hybrid engine, focusing on the interface between LLM-based reasoning and probabilistic logic.
• Engineering Excellence: Write and deploy high-availability production code in Java and Python, ensuring adherence to security and scalability standards.
• Evaluation & Tooling: Maintain and extend our internal evaluation and validation frameworks, including synthetic data generation, automated metric tracking, and model explainability.
• Clinical Collaboration: Work with Medical Experts and AI Engineers to translate complex medical requirements into technical specifications.
• Documentation: Provide technical documentation of AI components for stakeholders and regulatory compliance (e.g. SaMD).

What you’ll bring

• A Master’s degree in a quantitative field (Computer Science, Statistics, Mathematics, Physics, or similar). A PhD is a plus but is not essential.
• 3+ years of (industry) experience in AI/ML or algorithmic development.
• Proficiency in Python (mainly for AI/Logic) and Java (mainly for backend services).
• Practical experience with classic ML and algorithms, such as Probabilistic Graphical Models (PGMs).
• Hands-on experience with LLMs (ideally including RAG and Agents). Bonus points for exposure to their validation in production.
• Solid grasp of modern DevOps (Containerization, CI/CD, Automated Testing) and AI-assisted development (e.g., Cursor, Claude Code).
• A high degree of autonomy and a preference for collaborative peer reviews and documentation.
• Experience working in cross-functional teams, with a strong foundation in mathematics, logic, or statistical modelling to support rigorous problem-solving would be advantageous.
• Exposure to the healthcare sector or other regulated environments (e.g., ISO 13485, MDR, SaMD), along with familiarity in areas such as Kotlin, advanced data visualisation, or MLOps would be highly beneficial.

What’s awaiting you at Ada

• Flexible working hours to maintain a healthy work/life balance
• 28 days holiday, plus bank holidays to unplug, rest and recharge for our UK employees (30 days plus public holidays in Germany).
• Corporate health insurance and pension scheme (UK).
• Support to set up your home office space, with the option for a co-working space subscription for our remote employees.
• Parental benefits (Plus Nursery Benefits for the UK).
• Employee Assistance Programs to help you look after your emotional wellbeing and deal with life’s challenges.
• Stay active and healthy with a discounted ClassPass membership (or Urban Sports Club membership for our employees in Germany).
• Bike Leasing Scheme (Germany).
• Online Academy for learning and development opportunities.

At Ada, inclusivity isn't just a goal – it's our foundation. 

As a proud equal opportunity employer, we embrace diversity in all its forms. We encourage applications from every corner of society, regardless of race, color, religion, sex, pregnancy status, national origin, age, physical and mental abilities, marital status, sexual orientation, gender identity, gender expression, genetic information, and any other characteristic protected by law. 

Join us in shaping a more inclusive tomorrow.

Please note that we do not accept applications sent via email. All applications need to be completed using the online form.

 All your information will be kept confidential according to GDPR guidelines.

*Any commercial activities concerning this advertisement will not be appreciated.

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

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

 Consulting & Client-Facing Skills

Operational Readiness & Soft Skills

• In a fast-paced consulting environment, where no two days are the same, flexibility and problem-solving comes naturally to you. Furthermore, resilience and thriving on challenges are essential traits in our industry;

What do we offer?