Senior Machine Learning Engineer
3 weeks ago
We are looking for a
Senior Machine Learning Engineer
Location: London
The role
As a Senior Machine Learning Engineer, you will be part of our newly formed cross-functional squads that consist of people from different job functions across Rightmove including Machine Learning Engineers, Data Scientists, Software Developers, Machine Learning Ops Engineers, and a Product Owner. The squads are collaborative, ambitious, and determined teams that work with a high degree of autonomy and velocity, and value innovation and impact. They sit within the Data and Analytics Team, which is part of the Product Development organisation and plays a pivotal role in delivering exciting solutions.
Last year Rightmove launched a project called RAID (Rightmove AI Discovery) which was an opportunity to successfully explore, experiment and innovate with generative AI. The outputs from RAID, combined with the prioritised Hackathon ideas have contributed to our future product roadmaps and we are looking for a Senior Machine Learning Engineer to build efficient, data-driven AI systems that advance both our prediction automation and generative AI capabilities.
We are proud to be a team that is currently growing and enriching its data and data science capabilities to deliver effective and impactful solutions in an industry that is exciting, interesting, relevant, and challenging. You will be taking an active part in our AI platform - driving the development, implementation and scale-up of algorithms for measurable impact across the business, and creating the tools, frameworks and infrastructures that enables the acceleration of both delivery and optimisation of machine learning and generative AI products.
Join us in our exciting journey as we push the frontiers of Machine Learning and Generative AI. Your expertise and contributions will be invaluable in shaping the future of our AI capability and platform.
A typical week as a Senior Machine Learning Engineer might involve
Leading the effort to design, build, implement, and scale the end-to-end architecture for traditional machine learning and generative AI models. Collaborating with data engineers and software engineers to build scalable and reliable infrastructure, as part of our unified data platform (Data Hive) that supports diverse machine learning workloads. Working with large datasets, clean and pre-process data, and engineer features to make them suitable for machine learning models. This may involve data cleaning, normalization, and handling missing values. Acting as a bridge between data scientists who may not have the experience of building scalable systems, and backend engineers who may lack experience with machine learning or generative AI based systems Actively engage in all aspects of model development, from ideation and experimentation to deployment Support defining priorities and roadmap – deciding what we need first and what we need to build vs. what to buy, in partnership with other teams. Collaborating with senior management and key stakeholders in identifying and prioritising actionable, impactful insights across a variety of core business fronts, driving informed decision-making across the business and, hence, enhancing Rightmove’s capability to achieve goals and objectives Provide support to various data projects and OKRs such as contributing to the exciting data engineering development of Rightmove’s unified data platform – Data HiveWe’re looking for someone who can:
Accomplished and driven Senior Machine Learning Engineer who also has a good understanding of large language models and generative AI Translate the latest research into high-performing systems and models that can be practically applied to enhance user experience Apply techniques like fine-tuning and transfer learning to adapt pre-trained generative models to specific tasks or domains Foster an obsession with quality and engineering excellence through automated repeatable processes Experience of MLOps and GenAIOps frameworks and standards for robust embedding of machine learning and large language models Has good knowledge of data structures, data modelling and software architecture Help shape the future of AI at Rightmove by providing valuable feedback and contributing to tool improvements Develop methods to explain and interpret the decisions made by generative models, especially in scenarios where transparency is crucial Has a relentless passion to learn more and go deep into machine learning and generative AI concepts Maintain best practices for model development including deployment process, documentation, and coding standards Confidently contribute to technical and product discussions and share knowledge and ideas with colleagues across the company Exceptional communication skills, collaborates and delivers results as they work Look at the ‘big picture’ and understand where the value is for the business. Analyse user needs, understand where the gaps are, and contribute to leading change across Rightmove to adopt data science practices Open to constructive feedback and is both a leading individual and team contributor Curious and has a creative mind coupled with first rate critical thinking skills The ability to challenge and question ideas, openly and honestly, whilst providing solutions and options Ongoing professional development in machine learning and AI domains is expectedWe would love someone to have any of the following
A Bachelors degree, MSc or PhD in Computer Science, Mathematics, Computational Statistics, Machine Learning, or related STEM field 5+ years of relevant machine learning and data engineering experience within a fast-paced complex business setting Expertise in understanding and implementing generative models, such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and autoregressive models like Transformers Professional experience in SQL and Python beyond scripting; knowledge of basic paradigms (e.g. Object-orientated programming), related tools (e.g. Git) and core libraries and deep learning frameworks (e.g. PyTorch, Tensorflow, Keras); cloud technologies, particularly GCP; experience with ML pipeline orchestration tools; deployment experience overseeing end to end ML lifecycle. Comfortable working in a dynamic environment where generative AI is evolving as a key offering. Worked on projects involving the simultaneous generation of multiple types of data, such as images and text, pushing the boundaries of what generative models can achieve Impact-driven on the business, product, users and very importantly your colleagues as well Commercially minded and can put numbers into a business perspective and have experience of working in a fast-paced environment to drive growth Self-starter mindset Strong interpersonal skills, comfortable working with multiple stakeholders Proactive in seeking and giving caring and constructive feedbackUltimately, we care much more about the person you are, how you think and approach things, than a list of qualifications and buzzwords on a CV. Even if you can’t say ‘yes’ to all of the above, but are self-motivated and passionate about data then get in touch.
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