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LEAD MACHINE LEARNING ENGINEER

EU Remote

THE COMPANY
A global technology business operating at significant scale is looking to expand its Machine Learning capability. Their ML function sits at the core of the business, owning end-to-end machine learning systems that power critical commercial outcomes. They foster a collaborative engineering culture where experimentation, ownership, and technical excellence are highly valued.

THE ROLE

• Lead the technical direction of machine learning initiatives, helping shape architecture, best practices, and long-term strategy
• Design, develop, and optimise predictive machine learning models used in large-scale production environments
• Scale ML infrastructure including feature stores, training pipelines, model lifecycle management, and experimentation frameworks
• Drive the performance of real-time inference systems, balancing latency, scalability, and model accuracy
• Own end-to-end MLOps processes including monitoring, model performance evaluation, drift detection, and automated retraining
• Partner closely with engineering, analytics, and commercial stakeholders to translate business objectives into impactful machine learning solutions

YOUR SKILLS & EXPERIENCE

• Strong commercial experience building and owning production machine learning systems at scale
• Expertise in Python and modern machine learning frameworks such as PyTorch or TensorFlow
• Experience deploying and optimising real-time machine learning systems in production environments
• Strong understanding of MLOps, experimentation, model monitoring, and machine learning infrastructure
• Excellent software engineering fundamentals and experience writing production-quality code
• Ability to communicate complex technical concepts to both technical and non-technical stakeholders

WHAT THEY OFFER

• Competitive salary with performance-based bonus
• Flexible hybrid working model
• Enhanced wellbeing and mental health support
• Additional leave and flexible working benefits
• Strong learning and development environment
• Opportunity to influence machine learning strategy within a high-impact engineering team

HOW TO APPLY
If you’re a Machine Learning Engineer looking for a role that combines technical leadership, large-scale machine learning, and real-world impact, please apply today for more information.

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PRODUCT MANAGER, AI & DATA PRODUCTS

London (Hybrid)

THE COMPANY
An innovative data and insights business that helps organisations better understand consumer behaviour through advanced analytics and emerging technologies. They are investing heavily in AI-powered products and offer a highly collaborative environment where Product Managers have significant ownership and influence. This is an opportunity to join at a pivotal stage of growth and play a key role in defining future product strategy.

THE ROLE

• Own the product strategy and roadmap for AI and data-driven insight products, driving their evolution from concept to scalable commercial solutions
• Lead product development across dashboards, reporting tools, insights products, and client-facing platforms
• Take ownership of a consumer app and user experience, improving engagement, onboarding, retention, and data collection processes
• Work closely with engineering, data science, analytics, and commercial teams to prioritise product development and delivery
• Translate client and market needs into clear product requirements and commercially valuable features
• Support go-to-market activity through product documentation, demonstrations, stakeholder engagement, and roadmap communication

YOUR SKILLS & EXPERIENCE

• Strong commercial Product Management experience within data, analytics, SaaS, insights, research, martech, adtech, or technology products
• Proven ability to turn complex datasets into clear, scalable products with tangible commercial value
• Experience working closely with technical, data, and commercial stakeholders
• Strong product strategy, roadmap ownership, prioritisation, and product discovery capabilities
• Excellent stakeholder management and communication skills
• Exposure to AI, LLMs, consumer data products, mobile apps, or digital analytics environments would be beneficial

WHAT THEY OFFER

• Hybrid working model with flexibility
• Opportunity to define and shape a market-leading AI product proposition
• High levels of ownership and visibility across the business
• Collaborative, entrepreneurial working environment
• Strong opportunities for progression as the product function grows

HOW TO APPLY
If you’re a Product Manager looking to build innovative AI and data products while influencing business strategy, please apply today for more information.

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DATA SCIENTIST, DECISION SCIENCES

London OR Cossington (Hybrid)

THE COMPANY
A data-driven consumer business with a large and engaged customer base is seeking a Data Scientist to join their Decision Sciences team. They are investing heavily in advanced analytics and machine learning, with data playing a central role in strategic decision-making across the organisation. You’ll work in a collaborative environment alongside analytics, marketing, and commercial stakeholders, delivering solutions that have a tangible impact on customer outcomes.

THE ROLE

• Build and develop machine learning models focused on customer retention, churn prediction, and customer lifetime value
• Evaluate and improve existing modelling pipelines to increase accuracy and commercial impact
• Partner with CRM and marketing teams to translate model outputs into actionable retention strategies
• Develop forecasting and marketing effectiveness models to support business planning and decision-making
• Design, analyse, and interpret A/B tests and experimentation frameworks
• Deliver insight through deep-dive analysis, dashboards, and clear communication to stakeholders

YOUR SKILLS & EXPERIENCE

• Strong commercial experience as a Data Scientist within marketing, ecommerce, customer, loyalty, or membership environments
• Advanced Python and SQL skills, with experience working in modern data environments
• Strong understanding of statistical modelling, experimentation, and causal inference
• Experience building and deploying predictive machine learning models
• Ability to communicate technical findings to non-technical audiences
• Experience working closely with CRM or lifecycle marketing teams is advantageous

WHAT THEY OFFER

• Competitive salary plus bonus
• Hybrid working and flexible hours
• Private healthcare and enhanced pension package
• Additional annual leave and wellbeing benefits
• Ongoing learning and development opportunities
• Clear career progression within a growing data team

HOW TO APPLY
To find out more about this Data Scientist, Decision Sciences opportunity, please submit your CV for consideration.

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Databricks QA Engineer

Remote (UK) | £50,000 – £60,000 + Benefits
Must have full UK working rights

Are you a Data QA Engineer with strong Databricks and PySpark experience looking for a role where you can make a genuine impact? This is an opportunity to join a growing data function at a pivotal stage of its data transformation journey, helping to shape testing standards, improve data quality practices, and ensure the successful delivery of a modern cloud-based data platform.

The Company

This organisation is investing heavily in its data capabilities and building a modern data platform to support business-wide decision making. They have a collaborative culture where data teams work closely with stakeholders across the business to deliver high-quality, reliable solutions. With significant projects underway, they are looking for an experienced Data QA Engineer who can bring expertise, ownership, and a proactive approach to quality assurance.

The Role

As a Data QA Engineer, you will play a key role in ensuring the quality, reliability, and performance of a cloud-based data platform and associated products.

Responsibilities include:

• Designing, executing, and maintaining testing activities across data platforms and data products
• Performing functional, integration, regression, and data validation testing
• Working closely with Data Engineers, Analytics Engineers, and business stakeholders to identify risks and ensure robust solutions
• Developing testing strategies and helping define quality standards across the team
• Driving continuous improvement in testing processes, tools, and frameworks
• Managing defects through investigation, tracking, and resolution
• Working within a Databricks and PySpark environment, contributing to both testing and development activities
• Providing guidance and best practice recommendations around quality assurance and testing approaches
• Supporting the successful delivery of a large-scale data and analytics programme

Your Skills & Experience

You will bring:

• Strong commercial experience within Data QA, Software Testing, or Quality Engineering
• Experience testing data platforms, data pipelines, and complex technical solutions
• Hands-on experience with Databricks
• Strong PySpark, SQL, and Python skills
• Experience collaborating with both technical teams and business stakeholders
• Knowledge of testing methodologies, defect management, and quality assurance best practices
• Experience working within Agile delivery environments
• Exposure to CI/CD pipelines and modern data engineering practices would be advantageous
• Excellent communication skills with the confidence to challenge, influence, and drive improvements where required

What They Offer

• £50,000 – £60,000 base salary
• Comprehensive benefits package
• Remote-first working model
• Flexible-by-choice working policy designed around work-life balance
• Opportunity to influence testing standards within a growing data team
• Exposure to modern technologies including Databricks, PySpark, SQL, and Python
• Career development within a business investing heavily in data and analytics

How to Apply

If you’re a Data QA Engineer with Databricks, PySpark, SQL, and Python experience and are looking for a role where you can shape quality standards whilst working on a modern data platform, apply today.

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Senior AI Engineer – Remote

Join a growing AI team building production-grade machine learning and generative AI solutions that solve complex real-world challenges. This is an opportunity to combine AI research, engineering, and innovation in a highly autonomous role.

The Company
They are a technology business investing heavily in AI, with a focus on developing advanced machine learning, generative AI, and agentic systems. The environment is research-led, collaborative, and focused on turning cutting-edge ideas into scalable products.

The Role

• Design and deploy machine learning, deep learning, and LLM-based solutions
• Build RAG pipelines, agentic AI systems, and model evaluation frameworks
• Work across the full AI lifecycle from problem definition to deployment
• Apply both classical ML techniques and modern AI approaches
• Use AI-assisted development tools such as Claude Code, Codex, or similar
• Help shape technical direction and mentor other engineers

Your Skills & Experience

• Strong commercial experience across machine learning and generative AI
• Hands-on expertise with Python, PyTorch, Scikit-learn, and Hugging Face
• Experience building production AI systems and MLOps pipelines
• Practical use of AI coding assistants and agentic engineering workflows
• Ability to own projects independently from concept to delivery
• MSc required, PhD advantageous

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Data Engineer – Hybrid in San Francisco – $130,000-150,000

About the Opportunity

We are seeking a Data Engineer to join a growing data team and help scale the data foundation of a rapidly expanding business. This is a high-impact role supporting critical operational functions across manufacturing, inventory management, project delivery, and business operations.

Reporting to the Analytics Engineering function, you will own and enhance core data pipelines, improve data quality and visibility across business systems, and help stakeholders make better operational decisions through reliable, accessible data.

This position offers significant ownership, autonomy, and exposure to leadership as the organization continues to scale.

What You’ll Do
Data Engineering & Pipeline Development

• Own, maintain, and optimize approximately 20 existing production data pipelines.
• Design, build, and deploy new data pipelines to support business growth and evolving operational requirements.
• Develop and maintain scalable ETL/ELT processes across multiple business systems.
• Monitor data workflows, troubleshoot issues, and ensure high levels of reliability and accuracy.
• Improve data architecture, data quality, and pipeline performance.

Operational Data & Systems

• Integrate data from ERP, project management, design, manufacturing, inventory, and operational systems.
• Ensure source system accuracy and integrity to support reporting and decision-making.
• Build solutions that provide visibility into manufacturing output, inventory levels, project status, and operational performance.
• Ingest and manage public datasets to support strategic business initiatives and market analysis.

Cross-Functional Partnership

• Partner with stakeholders across operations, manufacturing, supply chain, project management, and business teams.
• Gather requirements, identify opportunities for automation, and deliver actionable data solutions.
• Translate technical concepts into clear business insights for non-technical stakeholders.
• Serve as a trusted partner helping teams leverage data to improve efficiency and execution.

What Success Looks Like
During your first 6 to 12 months, you will:

• Become the primary owner of critical operational data pipelines.
• Improve visibility into key manufacturing and inventory workflows.
• Increase confidence in source-system data quality and reporting accuracy.
• Build new data products and integrations that help teams scale efficiently.
• Create stronger data connectivity across operational functions and business stakeholders.

Required Qualifications

• 2-4 years of experience in Data Engineering, Analytics Engineering, or a related field.
• Advanced SQL skills with a strong understanding of relational databases.
• Experience building, maintaining, and scaling data pipelines and ETL/ELT processes.
• Strong communication and stakeholder management abilities.
• Ability to work independently in a fast-paced, high-growth environment.
• Proven track record of owning problems end-to-end and delivering business impact.
• Experience working across multiple domains rather than a narrowly specialized technical scope.

Preferred Qualifications

• Experience working with ERP platforms, particularly NetSuite or similar enterprise systems.
• Experience with transactional databases and operational business systems.
• Proficiency in Python.
• Experience with dbt, Spark, Databricks, or modern data platforms.
• Experience integrating APIs and third-party data sources.
• Familiarity with TypeScript or software engineering fundamentals.

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Data Engineer

Up to £70,000 + Benefits
Central London (Hybrid Working)
This is a fantastic opportunity to join a purpose-driven organisation where you can take ownership of building and developing a modern cloud-based analytics platform that supports data-driven decision-making across the business.

THE COMPANY:

Operating at the heart of the music industry, you will be part of an ongoing digital transformation programme, the business is investing heavily in its cloud-based Analytic Data Platform, creating an opportunity to work with cutting-edge data technologies while contributing to a platform that delivers real-world impact.

THE ROLE:

Key responsibilities include:

• Designing, building and maintaining scalable data pipelines and integrations.
• Developing robust ETL and data transformation processes to support analytics and reporting requirements.
• Working with Snowflake, DBT, Apache Airflow, AWS, SQL and Python to deliver high-quality data solutions.
• Collaborating with Data Architecture, DevOps and business stakeholders to ensure trusted and accessible data across the organisation.
• Contributing to engineering best practice, automation, testing, documentation and continuous improvement initiatives.

YOUR SKILLS AND EXPERIENCE:

You will bring strong capability in:

• SQL and Python development.
• Building and maintaining ETL/data pipelines in production environments.
• Cloud-based data platforms, ideally within AWS.
• Data modelling, transformation and orchestration methodologies.
• Delivering high-quality, well-documented and thoroughly tested data solutions.
• Experience with Snowflake, DBT and Apache Airflow.
• Interest in AI and emerging technologies within the data engineering landscape.

THE BENEFITS:

You will receive a salary of up to £70,000 depending on experience, along with a comprehensive benefits package.

HOW TO APPLY:

Please register your interest by sending your CV to Molly Bird via the apply link on this page.

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The Role

We are looking for a Technical Architect to take joint ownership of two critical dimensions: shaping the architecture of our platform and providing hands-on technical leadership to our engineering team. You will be a key decision-maker in how we build, scale, and evolve our systems – balancing technical excellence with practical delivery.
You will work closely with engineering, AI/ML, and product teams, and you will have a direct impact on the technology roadmap of a fast-growing startup in a highly regulated and meaningful space.

Responsibilities

Systems Architecture

• Design and evolve the overall platform architecture – backend services, ML inference pipelines, and clinical integrations – ensuring scalability, security, and performance.
• Define and enforce architectural patterns, coding standards, and technology decisions with a long-term perspective.
• Evaluate and select technologies, frameworks, and tools, clearly articulating trade-offs to both technical and non-technical stakeholders.
• Ensure architecture decisions account for the regulatory requirements of the medical device space (MDR, FDA SaMD).
• Lead the technical design of integrations with hospital systems (PACS, HIS) using standards such as DICOM and HL7/FHIR.
• Own non-functional requirements: reliability, latency, data privacy (GDPR, HIPAA-aligned), and disaster recovery.

Technical Leadership

• Be the technical reference for the engineering team: code reviews, mentoring, and establishing engineering best practices.
• Collaborate with the AI/ML team on the productionisation of inference models and the optimization of the end-to-end ML pipeline.
• Contribute to sprint planning and technical estimation, helping the team break down complexity into deliverable increments.
• Proactively identify and mitigate technical risks, communicating them clearly before they become blockers.
• Foster an engineering culture centred on quality, automation, observability, and continuous improvement.

Requirements

Must-haves

• 5-8 years of software engineering experience, with at least 2-3 years in architecture or senior technical leadership roles.
• Proven experience designing and operating cloud-native systems on AWS (compute, storage, networking, managed services, IAM).
• Strong background in Python for production environments – APIs, data processing pipelines, and ML model integration.
• Solid understanding of containerisation (Docker) and orchestration in production environments.
• Deep knowledge of distributed systems design principles: microservices, event-driven architecture, API design, and data consistency patterns.
• Experience building CI/CD pipelines and driving DevOps practices across an engineering team.
• Ability to document and communicate architecture decisions clearly, both in writing and in technical discussions.
• Comfortable operating in a startup environment: autonomous, pragmatic, and able to balance ideal solutions with real constraints.

Nice-to-haves

• Experience deploying and optimising ML models in production – including ONNX Runtime or similar inference frameworks.
• Familiarity with medical imaging standards: DICOM, HL7, FHIR.
• Background in regulated environments (MDR, FDA 21 CFR Part 11, ISO 13485, or similar).
• Experience with MLOps practices: model versioning, drift monitoring, and retraining pipelines.
• Knowledge of PHP/Laravel or experience working with and evolving an existing codebase built on it.
• Prior experience in healthtech, medtech, or other highly regulated industries.

What We Offer

• Competitive salary aligned with your experience and the market.
• Hybrid model with real flexibility – we care about outcomes, not hours.
• Direct, visible impact: your work shapes tools that help clinicians make better diagnoses.
• Small, highly skilled team with strong technical autonomy.
• Annual budget for training, conferences, and certifications.
• Freedom to challenge the status quo and propose improvements to how we build things.
• A collaborative, mission-driven environment where engineering is taken seriously.

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ML Scientist / Researcher

Oncology AI · Foundation Models · Life Sciences

Remote

About the Role

We are building foundation models trained on human tumor biology – one of the most consequential and technically demanding challenges at the intersection of AI and medicine. As an ML Scientist, you will be a core research contributor designing and training these models across multimodal omics datasets, partnering closely with biologists and fellow research scientists to advance the state of the art in oncology AI.

This is a research-forward role for scientists who want their work to matter. We are looking for people with a track record of research excellence – those who have gone deep on model architecture, training dynamics, and rigorous experimental design. If you have built models from the ground up and published findings, we want to talk.

What You’ll Do

• Design and train large-scale foundation models on multimodal biological datasets, including genomics, transcriptomics, and other omics modalities
• Collaborate deeply with computational biologists, research scientists, and domain experts to translate biological questions into tractable modeling problems
• Drive the full research lifecycle: hypothesis formation, experimental design, model development, and rigorous analysis of results
• Contribute to agentic AI systems that reason over complex biological data
• Communicate findings internally and, where appropriate, through peer-reviewed publication

What We’re Looking For

Must-Haves

• Strong research background, typically evidenced by a PhD in machine learning, computational biology, statistics, physics, or a related quantitative field – or equivalent industry research experience
• Demonstrated ability to build and train models end-to-end, including experimental analysis and iteration
• Research excellence: first-author publications at top ML, AI, or computational biology venues are a strong positive signal
• Deep familiarity with foundation model concepts: pretraining, self-supervised learning, attention mechanisms, and large-scale training
• Comfort working at the intersection of biology and machine learning – even without a formal biology degree

Nice-to-Haves

• Experience with biological or omics data (genomics, proteomics, pathology imaging, etc.)
• Prior work in multimodal learning or multi-omics integration
• Familiarity with agentic AI systems or tool-use frameworks
• Background in oncology or disease biology

What This Role Is Not

This is not a production ML engineering or MLOps role. We are not looking for candidates whose primary experience is model deployment, serving infrastructure, or engineering-heavy systems work. The emphasis here is firmly on research depth and model development.

Compensation & Location

Base Salary: $250,000 – $288,000 (depending on experience) + equity

Location: Remote-friendly; office in South San Francisco, CA

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