Lead Machine Learning Engineer

London, ENG, GB, United Kingdom

Job Description

Help us use technology to make a big green dent in the universe!

Kraken powers some of the most innovative global developments in energy.

We're a technology company focused on creating a smart, sustainable energy system. From optimising renewable generation, creating a more intelligent grid and enabling utilities to provide excellent customer experiences, our operating system for energy is transforming the industry around the world in a way that benefits everyone.

It's a really exciting time in energy. Help us make a real impact on shaping a better, more sustainable future.

Kraken Utilities



Our tech platform 'Kraken' is already licensed to support 55 million customer accounts globally, and we aim to serve 100 million by 2027. Kraken is the most AI-driven, innovative, forward-thinking platform for energy management. From optimising resources to delivering cost-effective, exceptional customer experiences through advanced Customer Information Systems (CIS), billing, meter data management, CRM, and AI-driven communications.

We're now charging the Kraken platform to other utility industries (Water and Broadband) and have created a new team called - Kraken Utilities. Over the last 2 years we have built this team from scratch to re-architect, design, and develop our Kraken software platform to solve complex industry wide problems within the water and broadband sectors (such as customer experience & water leak detection).

The Kraken Utilities team is in a very exciting growth phase, and has already signed 5 clients; Severn Trent, Leep, Portsmouth Water, TalkTalk and Cuckoo. We are currently 120+ people (engineers, product, implementation, strategy) along with 1800+ people in the overall Kraken world.

The role

Kraken is the operating system for utilities of the future. Built in-house at Octopus Energy, we took them to become the biggest supplier in the UK, and now we power energy, water and telco companies around the globe - in 10 countries and counting, licensing software to giants like Origin Energy in Australia and Tokyo Gas in Japan. We're on a mission to accelerate the renewable transition, and bring affordable green energy to the world.

We've reinvented energy products with smart, data driven tariffs to balance customer demand with renewable generation, and Kraken's platform controls more than half of the grid-scale batteries in the UK. We're revolutionising the utilities industry and are excited about how Kraken can transform both the customer experience and operational efficiency for our clients.Our platform allows our specialists to be the most productive in the industry, with our suite of AI tools making us pioneers in using ML and AI to make agents' lives easier and customers happier.

We do it by hiring clever, curious, and self-driven people, enabling them with modern tools and infrastructure and giving them lots of autonomy. Our ML team consists of ML, front-end and back-end engineers, so that we can rapidly prototype and get innovative tools in use at breakneck speed.

We've had great success in using AI to bring better service to customers, and we want to bring that success to the whole business. You'll manage a small expert team working on the most pressing problems for the business, whether it's internal AI tooling to make our developers twice as productive, or automating processes to improve efficiency of our business. You'll work across the whole product lifecycle: identifying uses of new technologies via exploration, working closely with teams around the business to validate that your ideas will bring value, and rapidly prototyping. The work you do will define the pattern for AI success at the company.

You'll have wide open problems to solve, so you'll need to be comfortable with ambiguity, figuring out an approach and validating it fast. You'll stay up to date with changes in the field, using your knowledge of state-of-the-art techniques to solve problems. LLMs will be your bread and butter, customized with advanced RAG techniques, finetuning and reinforcement learning. You'll work closely with other engineers to build fast, and you'll use Python and Kubernetes to deploy systems in production.

What you'll do:



Manage a high performance team of LLM, MLOps, backend and front end engineers Collaborate closely with cross-functional stakeholders -- including product managers, client delivery leads, support teams, and business operations -- to align technical initiatives with business goals Tackle the biggest problems facing the company, giving a wide experience across the business, with the freedom to define novel approaches Develop systems that enable LLMs to understand and interact with the millions of lines of code that power Kraken, as well as the complex business rules, operational processes, and terabytes of structured and unstructured data behind it -- using cutting-edge techniques like GraphRAG, agentic workflows, finetuning, and reinforcement learning Design systems that assist developers, support agents, migration teams, and more -- creating AI agents for every part of the business Use classic ML and NLP techniques to complement and improve LLM systems Deploy and monitor ML systems in production using Python and Kubernetes Be on the forefront of understanding AI advancements and their technical implications for the team and business

What you'll need:



Curious and self driven - in a field that changes so quickly, its essential you have the initiative to make decisions yourself, and can find solutions to novel problems without lots of help and support Prior experience managing a small team (3-5 ML engineers). 2+ years of hands-on experience deploying LLMs in production (not just POCs), including techniques like RAG, tool calling, finetuning, and RLHF 8+ years of experience in classic ML and NLP, including training, deployment, monitoring, and feedback-driven iteration A keen interest in Gen AI and classic ML, understanding of emerging trends and research, and proven experience aligning and applying this to real world objectives Proven ability to align AI solutions to concrete business outcomes

It would be a bonus if you have:



Experience working with large codebases and collaborating with multiple engineering teams in large companies Experience in diverse LLM deployment methods (eg hosted finetuned models via services like Bedrock, and running directly via engines like LLM)

This team will require you to work on a hybrid remote basis, coming into our office in London Oxford Circus 2 days a week.

We're very excited to be growing our team. We're looking for skills and experience to help shape and define the future of not only our team, but the wider business at a global scale. If you're reading this and grinning, please apply! There are huge challenges to tackle, and we need amazing people who are keen to get stuck in. Are you ready for a career with us? We want to ensure you have all the tools and environment you need to unleash your potential. Need any specific accommodations? Whether you require specific accommodations or have a unique preference, let us know, and we'll do what we can to customise your interview process for comfort and maximum magic! Studies have shown that some groups of people, like women, are less likely to apply to a role unless they meet 100% of the job requirements. Whoever you are, if you like one of our jobs, we encourage you to apply as you might just be the candidate we hire. Across Kraken, we're looking for genuinely decent people who are honest and empathetic. Our people are our strongest asset and the unique skills and perspectives people bring to the team are the driving force of our success. As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. Our commitment is to provide equal opportunities, an inclusive work environment, and fairness for everyone.

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Job Detail

  • Job Id
    JD3388463
  • Industry
    Not mentioned
  • Total Positions
    1
  • Job Type:
    Full Time
  • Salary:
    Not mentioned
  • Employment Status
    Permanent
  • Job Location
    London, ENG, GB, United Kingdom
  • Education
    Not mentioned