16 jobs in Omnis Partners

Global Data Science Director

Global Consumer Brand

Location - London, Hybrid

Compensation is as follows:

• £200,000 per annum
• 20% annual bonus
• Equity participation

Omnis has been exclusively retained to identify a Global Consumer Data Science Leader for a globally recognised consumer brand.

Whilst operating at significant global scale, the organisation has retained a highly collaborative, ambitious and entrepreneurial culture, with strong executive sponsorship for data, analytics and AI transformation initiatives. The business combines exceptionally high standards with genuine partnership, bringing together outstanding operators, intellectually curious leaders and teams that are empowered to drive meaningful change.

The successful individual will lead a global practice f Data Science, Analytics and Engineering staff, with direct responsibility for two senior leaders, broader management and sub teams. The expectation is that this capability continues to grow significantly over the coming years as further functions are brought in-house.

The remit spans two core pillars of Customer Data Science and Marketing Measurement, with a strategic programme already underway to insource capabilities currently delivered by specialist consultancies and external partners. Alongside this sits responsibility for the evolution of emerging capability areas including pricing science, customer value optimisation and the application of AI across customer decisioning and engagement.

The role sits at the centre of a significant transformation agenda, with responsibility for shaping the future of customer intelligence and data science within the organisation. Over the next three years, key priorities include building graph-based customer intelligence capabilities, unlocking value from unstructured customer signals and feedback, supporting AI-powered recommendation and client engagement experiences, and helping define the next generation customer data and marketing technology ecosystem.

Equally important will be establishing how Data Science, AI Engineering and MLOps functions operate together in an AI-enabled business, whilst defining the long-term operating model for Consumer Data Science as the organisation continues its transformation.

The wider business is investing heavily across customer platforms, semantic layers, data infrastructure and enterprise transformation programmes, requiring an individual who is equally comfortable discussing modelling approaches, technology architecture and commercial outcomes.

Perhaps most compellingly, this is not an organisation looking to preserve the status quo. The leadership team is actively debating what future data science organisations should look like, how AI engineering and data science capabilities converge, and what skills will define success over the next decade.

Despite the scale of the business, there remains an unusual amount of white space, influence and opportunity to shape strategy, operating models and future investment decisions.

The successful individual will combine deep consumer data science expertise with exceptional communication skills, executive presence and the ability to influence senior stakeholders across regions, functions and disciplines.

For the right person, this represents an opportunity to shape not only the future of customer science within a globally recognised organisation, but also the role AI will play in defining the next generation of consumer experiences.

Senior AI Software Engineer

Agentic AI | Enterprise Deployment

Disruptive European AI Consulting Firm

Fully Remote

£90k - £160k - depending on experience

We're partnering with a profitable, fast-growing AI consultancy helping some of Europe's largest enterprises move AI from experimentation into production.

This business specialises in solving the difficult engineering challenges that emerge when AI becomes business-critical. Their work spans agentic systems, governance, observability, evaluation frameworks, security, monitoring and enterprise-scale deployment.

Founded by seriously impressive and well-networked leaders from top-tier consulting and transformation backgrounds, the business sits at the intersection of strategy, product and engineering , helping major financial services and insurance organisations deploy AI safely and effectively in complex real-world environments.

As demand continues to accelerate, they are looking to hire Senior AI Software Engineers who understand what happens after the demo works.

The Opportunity

This role is ideal for engineers who have already built and deployed production-grade AI systems and want to work on some of the most technically challenging problems in enterprise AI.

You'll be designing and building agentic systems, multi-agent architectures and AI-powered products used by large organisations, while helping establish the engineering standards required to operate these systems safely and reliably at scale.

What You'll Be Doing

• Designing and building production-grade AI applications powered by large language models
• Developing agentic systems, tool-calling frameworks and multi-agent workflows
• Building scalable backend services using modern Python and cloud-native technologies
• Designing evaluation frameworks and testing harnesses to measure AI quality and reliability
• Implementing observability, monitoring and tracing across AI systems
• Managing challenges such as hallucinations, prompt injection, latency and model drift
• Building secure, reliable deployment pipelines for enterprise environments
• Working directly with clients and stakeholders to deliver high-impact AI solutions

Experience Required:

• Production deployment of LLM-powered applications
• Multi-agent systems, orchestration frameworks and tool use
• Evaluation harnesses, benchmarking and AI quality measurement
• Langfuse, Braintrust or similar observability and evaluation platforms
• Prompt engineering, structured outputs and context management
• Python development and modern backend engineering practices
• Cloud infrastructure, containerisation and CI/CD
• Monitoring, debugging and operating AI systems in production environments

Why Join?

The AI industry is entering a new phase. The challenge is no longer whether AI models can generate impressive outputs; it's whether organisations can deploy them safely, reliably and at scale.

This business is operating at the centre of that transition, helping major enterprises solve challenges around governance, security, evaluation, monitoring and agentic AI deployment.

For ambitious engineers, this is an opportunity to work on some of the most important problems in enterprise AI today, alongside a highly technical team, within a profitable organisation experiencing significant demand and growth.

APPLIED ML SCIENTIST | REINFORCEMENT LEARNING Build Reinforcement Learning Systems For The Real World

Why is this exciting? Because this sits at the convergence of several areas that are becoming increasingly important:

• Physical AI
• Digital Twins & Simulation
• Federated Learning
• Edge AI
• Critical Infrastructure
• Sustainability

Most AI companies are building tools that generate content. This team is building AI that makes decisions in the real world.

Backed by fresh funding and entering a major growth phase, they're developing a new generation of AI systems capable of learning, adapting and optimising complex physical environments. Their first challenge? Reducing the energy consumption of data centres through reinforcement learning and distributed AI.

The problems are messy, ambiguous and genuinely difficult.

You'll be working with real telemetry, real constraints and real-world systems where model performance has a direct impact on energy efficiency, sustainability and operational outcomes. This isn't about tweaking prompts or wrapping foundation models. It's about building intelligent systems that can learn how the physical world behaves and make better decisions because of it.

They're looking for someone who combines strong machine learning fundamentals with the curiosity to understand how complex systems actually work. Someone who enjoys moving between research, experimentation and production, and gets excited by solving problems that don't already have a playbook.

You'll have the opportunity to work across reinforcement learning, simulation, federated learning and next-generation AI systems, helping shape technology that extends far beyond a single use case.

For the right person, this is a chance to join at a pivotal moment. The team is growing, the roadmap is ambitious, and the technical challenges are the kind that attract people who want to push the boundaries of what AI can actually do.

• Strong hands-on experience with Reinforcement Learning (RL)
• Python and modern ML frameworks (PyTorch, JAX, TensorFlow )
• Experience working with time-series or sensor data
• Ability to turn real-world problems into practical ML solutions
• Comfortable taking models from research into production
• Educated to degree level (or higher) in ML, Physics, Engineering, Mathematics or a related field

• Control systems, optimisation or simulation experience
• Federated Learning, Edge AI or Distributed ML
• Digital twins, thermodynamics or physical systems knowledge
• Safe RL, Offline RL, GNNs or Multi-Agent Systems
• MSc/PhD or published research in a relevant field

Someone who enjoys solving hard, real-world problems at the intersection of AI, engineering and physical systems.

Omnis Partners is seeking an Applied ML Scientist focused on building reinforcement learning systems for real-world applications. This role offers the opportunity to work on complex AI challenges that aim to improve energy efficiency and sustainability in data centers.

The ideal candidate will have strong experience in reinforcement learning and modern ML frameworks. This position promises to be pivotal as the team expands and takes on ambitious projects.

Join Omnis Partners to explore and push the boundaries of AI technology.

Associate Director - Data, Product and AI - Contract

Location: Hybrid 1-2 days per week onsite in London

Start: 24th November - 1 month initially but strong chance of extension

An established consultancy is seeking a Machine Learning Engineer (Contract) to support a global education organisation on an ongoing AI workspace project. The work will focus on extending internal tooling and integrating intelligent document management capabilities used across multiple regions.

This is a hands‑on individual contributor role, ideal for someone who enjoys working end‑to‑end from data and architecture through to deployment and knowledge transfer within a collaborative, agile delivery team.

• Develop and maintain project‑specific workspace functionality, including file storage, metadata and system prompt management.
• UI integration with collapsible sidebar navigation.
• Build or integrate a SharePoint or cloud‑based file environment, including permissioned repositories for business units to upload and access documents independently.
• Provide a pre‑defined library for initial deployment (e.g., finance or operational materials).
• Implement basic access controls, validation and testing.

• Strong proficiency in Python with experience in machine learning deployment and MLOps tooling.
• Understanding of SharePoint.
• Strong Azure, or similar cloud‑based storage and directory structures.
• Experience building document or knowledge management systems.
• Ability to work autonomously, taking ownership from design through to delivery.

Mid‑Senior level

Contract

Production

Industries: Business Consulting and Services and Education