Learning & Development Specialist (Fixed Term Contract)

Join Multiverse as an Additional Learning Needs (ALN) & Inclusion Specialist, where you will play a pivotal role in fostering an inclusive learning environment. You will work closely with diverse learners, ensuring that their unique educational needs are met and that they thrive within our innovative educational framework.

AVK SEG UK Ltd is hiring two Learning and Development Specialists to join the growing Learning and Development team in London. These roles play a key part in shaping employee growth and supporting the company’s evolving approach to learning and talent development. About AVK AVK powers the future of data as the largest provider of power solutions for data centers, AI infrastructure, and leading organizations across the UK and Europe. The company focuses on sustainable and innovative energy solutions that help redefine how the data center industry connects with power. Role Overview Both positions will work closely with business leaders, subject matter experts, and external partners to design and deliver learning programs that improve performance and prepare employees for future challenges. Role 1: Early Careers & Future Talent Lead Early Careers initiatives, including apprenticeships, graduate schemes, and trainee programs. Design learning curricula that balance technical skills, professional growth, and behavioral development. Manage relationships with training providers, colleges, and accreditation bodies. Oversee cohort management: development planning, progress tracking, and communication with stakeholders. Support managers in developing early-career colleagues. Role 2: Career Development & Technical Capability Create and maintain career development frameworks and progression pathways across the business. Work with subject matter experts to build structured technical learning paths. Facilitate workshops, programs, and blended learning experiences. Drive initiatives that embed knowledge sharing and encourage continuous learning. Develop scalable learning solutions that support business goals. Evaluate learning impact and improve offerings over time. Shared Responsibilities Work with stakeholders to identify learning needs and set priorities. Contribute to the Learning and Development strategy and roadmap. Use data and feedback to improve learning effectiveness. Promote a culture focused on learning, development, and strong performance.

Multiverse is a platform focused on upskilling in AI and technology, working with individuals and organizations to build digital capabilities. Based in London, Multiverse partners with more than 1,500 organizations and has helped learners generate over $2 billion in ROI for their employers through improved productivity and measurable results. In June 2022, Multiverse secured $220 million in Series D funding, led by StepStone Group, Lightspeed Venture Partners, and General Catalyst. This investment brought the company’s post-money valuation to $1.7 billion and established Multiverse as the UK’s first EdTech unicorn. The team now includes over 800 employees, all working toward a future where technology skills unlock opportunity for everyone. Role overview The Senior Learning Solutions Specialist shapes and adapts Multiverse’s core learning experiences and materials to fit the needs of clients and learners. This role directly influences client engagement and learner retention. What you will do Work with product and curriculum teams, sales leaders, and operational stakeholders to identify where learning materials can be customized. For complex projects, connect directly with clients to understand and address their specific challenges. Once changes are approved, coordinate resources and stakeholders to implement updates in learning materials. Support coaches and communicate changes clearly to both clients and learners. What you bring Experience adapting learning solutions or educational content to meet varied client needs. Strong understanding of how curriculum changes can drive measurable results, even if not an expert in every subject area. Ability to collaborate across teams and manage multiple stakeholders. Location This role is based in London.

Genetec Inc. seeks an EMEA Events Specialist to join the team in London. This position centers on organizing and delivering events across Europe, the Middle East, and Africa, aiming to build brand presence and connect with important audiences. Key responsibilities Plan, coordinate, and execute a variety of events throughout the EMEA region Collaborate with colleagues to ensure each event reflects Genetec’s brand objectives Support initiatives that engage attendees and help create lasting, positive experiences Location This role is based in London, England, United Kingdom.

About AnthropicAt Anthropic, we are dedicated to developing reliable, interpretable, and controllable AI systems. Our goal is to ensure that AI technology is safe and beneficial for both users and society. Our rapidly expanding team consists of passionate researchers, engineers, policy experts, and business leaders collaborating to create advantageous AI systems.About the TeamsThe Reinforcement Learning teams at Anthropic spearhead our research and development in reinforcement learning, playing an essential role in enhancing our AI systems. We have made significant contributions to all Claude models, particularly impacting the autonomy and coding capabilities of Claude Sonnet 4.5 and Opus 4.5. Our work encompasses several critical areas:Creating systems that empower models to utilize computers effectively.Enhancing code generation through reinforcement learning techniques.Conducting pioneering RL research for large language models.Establishing scalable RL infrastructure and training methodologies.Improving model reasoning capabilities.We work closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and secure. Additionally, we collaborate with the applied production training team to seamlessly integrate research advancements into deployed models, demonstrating our commitment to implementing research at scale. Our Reinforcement Learning teams operate at the intersection of cutting-edge research and engineering excellence, dedicated to building high-quality, scalable systems that expand the possibilities of AI.About the RoleAs a Research Engineer in the Reinforcement Learning domain, you will partner with a diverse group of researchers and engineers to enhance the capabilities and safety of large language models. This position merges research and engineering responsibilities, requiring you to implement innovative approaches while contributing to the research strategy. You will engage in fundamental research in reinforcement learning, developing 'agentic' models capable of tool use for open-ended tasks such as computer usage and autonomous software generation, improving reasoning skills in disciplines like mathematics, and creating prototypes for internal applications, productivity, and evaluation.Representative Projects:Design and optimize core reinforcement learning infrastructure, from clean training abstractions to distributed experiment management across GPU clusters, scaling our systems to manage increasingly complex research workflows.Invent, implement, and evaluate novel training environments, evaluations, and methodologies for reinforcement learning.

Role overview The Associate Learning Advisor at BrainStation in London supports students as they consider and move through various courses and programs. This position centers on helping learners make choices about their education and providing guidance throughout their experience with BrainStation. What you will do Advise students on selecting the right courses and programs Assist learners as they explore BrainStation’s educational offerings Help maintain a welcoming and supportive environment for students Requirements Interest in education and supporting student growth Clear communication and strong interpersonal abilities Dedication to helping learners achieve their objectives

Welcome to TOCA Social, the pioneering dining and entertainment concept that brings a unique football twist to your experience! Since opening our first venue at The O2 in London in 2021, we have expanded to three locations across the UK and are thrilled to announce our upcoming venue in Dallas, US, with plans for Paris, Mexico, and Guatemala by 2026!At TOCA Social, we believe that everyone should play! No prior football knowledge is necessary; if you thrive in a vibrant and entertaining atmosphere, you're bound to love our innovative concept!About the Role:Location: Hybrid, requiring travel to venue locations across the UK and Europe at least two times per week.Reports To: Global Talent Development & Learning LeadHours: 45 hours per week, with one day dedicated to completing the Level 5 Digital Learning Designer Qualification.Contract Length: 19 months, with potential for a permanent position based on business needs.Anticipated Start Date: April 2026.As TOCA continues to grow in both corporate and franchise markets, we are enhancing our learning systems to keep pace with operational changes while facilitating long-term leadership and capability development. The Learning Designer & Administrator Apprentice will be responsible for designing, maintaining, and reporting on learning content and platforms for both TOCA brands (Soccer and Social), ensuring that learning remains accurate, accessible, and relevant.This apprenticeship is tailored for individuals early in their learning or People & Culture career, providing the opportunity to work closely with our Global Talent & Development Partner and gain firsthand experience in a global learning and development role.Key Responsibilities:Learning Design & Content Maintenance:Creation and upkeep of operational learning materials across both TOCA brands, including:Classroom-based workshop materials (participation guides, facilitation guides, and tools for workshops).E-learning modules and structured learning pathways for team members.Job aids, SOPs, and assessments.New venue opening learning toolkits.Quickly and accurately updating training materials in response to operational changes, such as:Menu changes.Service updates.System and process modifications.New territory launches.LMS Administration:End-to-end management of TOCA’s global learning platforms, including:Maintaining clean and accurate learning pathways.Uploading, updating, and archiving learning content.Monitoring completion rates, engagement, and learner progress.Building quizzes, assessments, and knowledge checks.Ensuring data accuracy and platform governance.Reporting & Insight:You will support...

About UsFounded in the United States in 2022 and now headquartered in London, UK, Recraft is revolutionizing the creative landscape with its cutting-edge AI tool designed specifically for professional designers, illustrators, and marketers. Our platform sets a new benchmark in image generation excellence.Our innovative tool empowers creators to swiftly generate and refine original images, vector art, illustrations, icons, and 3D graphics using AI technology. With over 3 million users across 200 countries, who have collectively produced hundreds of millions of images, Recraft is just at the beginning of its journey.Join us and explore a universe of professional opportunities! Contribute to large-scale projects and help shape the future of creativity. We are dedicated to making Recraft an indispensable daily tool for every designer, setting the industry standard. Our mission is to enable creators to fully control their creative process with AI, equipping them with innovative tools to turn their ideas into reality.If you are enthusiastic about pushing the boundaries of AI, we welcome you to join our team!

Join datatonic as a Senior Machine Learning Engineer and be a pivotal part of our innovative team focused on transforming data into actionable insights. In this role, you will leverage your expertise in machine learning to develop and enhance algorithms, contribute to data-driven solutions, and collaborate with cross-functional teams to push the boundaries of data analytics.

At Intercom, we are revolutionizing customer service through artificial intelligence, empowering businesses to deliver outstanding customer experiences.Our AI agent, Fin, stands as the most sophisticated customer service AI agent available, allowing companies to provide continuous, flawless customer support, ultimately enhancing customer interactions. Fin seamlessly integrates with our Helpdesk to form the Intercom Customer Service Suite—a comprehensive solution that offers AI-augmented assistance for more complex or high-touch inquiries that necessitate human intervention.Since our inception in 2011, Intercom has earned the trust of nearly 30,000 businesses worldwide and is setting a new benchmark in customer service. Guided by our core values, we consistently push boundaries, work with speed and intensity, and deliver exceptional value to our clients.What’s the Opportunity?The Machine Learning team at Intercom is tasked with defining innovative ML features, researching suitable algorithms and technologies, and quickly delivering initial prototypes to our customers.Our team is deeply product-focused, collaborating closely with Product and Design teams. Our dedicated ML product engineers enable rapid transitions to production, often launching beta versions just weeks after successful offline testing.We are passionate about harnessing machine learning technology, having productized everything from traditional supervised models to cutting-edge unsupervised clustering algorithms and novel transformer neural network applications. We rigorously evaluate the real customer impact of each model we deploy.What Will I Be Doing?Identifying opportunities where machine learning can add value for our customers.Defining the appropriate ML framing for product challenges.Collaborating with teammates and stakeholders from Product and Design.Conducting exploratory data analysis and research.Gaining a deep understanding of the problem areas.Researching and selecting the most suitable algorithms and tools.Being pragmatic while pushing the boundaries of innovation when necessary.Performing offline evaluations to validate algorithm effectiveness.Working alongside engineers to transition prototypes into production.Planning, measuring, and sharing insights to guide iterative development.Collaborating closely with the team and others to create exceptional ML products.

Join Our Innovative Team as a Machine Learning ResearcherAt Wintermute, we are on the forefront of digital asset trading, leveraging cutting-edge technology to provide unparalleled liquidity and OTC solutions across the cryptocurrency landscape. As a technology unicorn founded in 2017, we are a leading player in algorithmic trading, committed to supporting high-profile blockchain projects and ushering traditional financial institutions into the exciting world of crypto. Our venture arm also invests in early-stage DeFi initiatives, fostering innovation in the blockchain space.Our culture merges the rigor of high-frequency trading with the innovative spirit of tech startups, creating an environment that champions both technological excellence and entrepreneurial ambition. We believe in the transformative potential of blockchain technology, maintaining a long-term vision for the digital asset market while prioritizing compliance and innovation.Your Role and ResponsibilitiesAs a Machine Learning Researcher, you will harness your expertise in applied deep learning to develop robust alpha signal generation pipelines. Your work will encompass everything from data ingestion and feature engineering to model training and deployment, all in close collaboration with our dynamic trading and infrastructure teams.

Join the prestigious Anthropic Fellows Program, where you'll have the opportunity to delve into cutting-edge research in Reinforcement Learning. This program is designed for individuals passionate about advancing AI safety and developing innovative solutions. As a fellow, you will collaborate with a team of experts, engage in impactful projects, and contribute to a progressive research environment.

Join datatonic as a Machine Learning Engineer and be part of a dynamic team dedicated to leveraging data to drive intelligent decision-making. You will design and implement machine learning models, optimize algorithms, and collaborate with cross-functional teams to deliver innovative solutions.

Waymo is a pioneering company in the field of autonomous driving technology, dedicated to becoming the most trusted driver in the world. Originating from the Google Self-Driving Car Project in 2009, Waymo has concentrated on developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and save lives lost to traffic accidents. The Waymo Driver supports our fully autonomous ride-hailing service and is adaptable across various vehicle platforms and applications. With over ten million rider-only trips and more than 100 million miles driven autonomously on public roads, complemented by tens of billions of miles in simulation across 15+ U.S. states, our experience is unparalleled.The Simulator team is at the forefront of creating cutting-edge simulations of real-world environments for the training and assessment of the Waymo Driver. We leverage machine learning to accurately model the real world, incorporating realistic agents (vehicles, pedestrians, cyclists, motorcyclists, etc.), road systems, traffic controls, and weather conditions. To enhance the precision and flexibility of our simulations, we utilize large foundation models trained on extensive datasets, enabling rapid setup and deployment of multiple scenarios for our driver.Our London-based team collaborates closely with our colleagues in Mountain View and Oxford to develop and enhance these foundation models and integrate them into various evaluation and training products. We are seeking talented research engineers eager to tackle these innovative challenges.In this hybrid role, you will report directly to an Engineering Manager.

Waymo, a pioneer in autonomous driving technology, is dedicated to becoming the world’s most trusted driver. Since its inception as the Google Self-Driving Car Project in 2009, Waymo has been at the forefront of innovation, developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility while significantly reducing the number of lives lost in traffic accidents. The Waymo Driver powers our fully autonomous ride-hailing service and is adaptable to various vehicle platforms and applications. With over ten million rider-only trips completed, fueled by our experience of autonomously driving over 100 million miles on public roads and tens of billions of miles in simulation across more than 15 U.S. states, we are transforming transportation.The Driver Understanding and Evaluation (DUE) team at Waymo is focused on creating comprehensive metrics to evaluate the Waymo Driver’s behavior in real-world scenarios. We are developing advanced technologies such as context and scene analysis to enhance our driving understanding, as well as augmenting real-world driving data to generate rare driving events. This includes building large-scale data infrastructures and improving components like agents and realistic simulators, which are pivotal for our technical strategies and methodologies in assessing the Waymo Driver's performance.The DUE Machine Learning team will develop and maintain scalable machine learning systems and simulation workflows, enhancing evaluation processes and developer onboarding experiences. By merging expert human insights with cutting-edge machine learning models, we will provide training and evaluation data across hundreds of metrics and components that define the Waymo Driver. We are seeking passionate researchers and software engineers eager to harness machine learning techniques to elevate the evaluation systems within our autonomous vehicles, driven by a relentless pursuit of performance improvement.This position reports to the Engineering Manager.

Join Trainline as the Head of Machine Learning Engineering, where you'll lead our innovative machine learning initiatives. In this pivotal role, you will spearhead the development and implementation of advanced ML solutions that enhance our customer experience and optimize our operations.

About the Position We are seeking intellectually curious and innovative individuals from both industry and academia to join our expanding Machine Learning team. In this role, you will develop deep learning models that enhance our trading strategies, leveraging our advanced computing cluster equipped with tens of thousands of high-performance GPUs. The unique challenges of trading, such as managing large models and dynamic datasets in a competitive multi-agent environment, will inspire you to explore and implement novel solutions. Our collaborative environment brings together researchers, engineers, and traders to work side by side, focusing on training models, designing systems, and executing trading strategies. Each day may involve analyzing market data, optimizing hyperparameters, troubleshooting distributed training performance, or examining how our models perform in live trading. Your expertise in the machine learning realm, including familiarity with various methodologies derived from LLMs, image models, reinforcement learning agents, recommendation systems, and traditional ML approaches, will be crucial in steering the future of ML at Jane Street. You will train models to support the next generation of our deep learning trading strategies and contribute to our foundational knowledge for navigating new markets and scenarios. Additionally, you will play a key role in recruiting new talent, attending industry conferences, and sharing your insights with teammates, all of which are vital aspects of this position.

About the Position We are seeking intelligent and inquisitive individuals to enhance our dynamic Machine Learning team at Jane Street. This role offers the opportunity to develop cutting-edge deep learning models that underpin our trading strategies, utilizing our expansive computing cluster equipped with tens of thousands of high-performance GPUs. The trading environment presents unique challenges, including large-scale models and nonstationary datasets within a competitive multi-agent landscape, prompting innovative solutions. At Jane Street, our researchers, engineers, and traders collaborate closely, sharing knowledge and expertise just a few feet apart. Your day may involve analyzing market data, optimizing hyperparameters, diagnosing distributed training performance, or exploring our models' behaviors in live trading scenarios. Your extensive knowledge of the machine learning domain and familiarity with diverse methodologies—ranging from LLMs, image recognition systems, RL agents, recommendation frameworks, to classical ML techniques—will be invaluable in advancing ML at Jane Street. You will play a crucial role in training models for our next-generation deep learning trading strategies and developing the insights necessary to navigate new markets and challenges. Furthermore, you will be involved in the recruitment of new team members, attending industry conferences, and sharing your expertise with colleagues, all of which are considered significant contributions to our mission.

Join Our Team as a Staff Machine Learning EngineerBecome an integral part of Deliveroo’s mission to revolutionize the shopping and dining experience with a focus on impact, innovation, and growth. Our talented Engineering teams tackle intricate technical challenges within a global, three-sided marketplace, developing and scaling systems that cater to millions of customers, riders, and partners daily.From advanced real-time logistics to robust infrastructure and marketplace optimization, we create and manage the technology that fuels Deliveroo’s expansive growth.We are seeking a Staff Machine Learning Engineer to join our dynamic London team (working in a hybrid model, 3 days in the office). In this pivotal role, you will design and construct intelligent decision-making systems that operate at a large scale, directly influencing the experiences of consumers, riders, and merchants.Explore our Engineering team and discover our motivations, work culture, and what you can expect as part of our community.Your ResponsibilitiesJoin the Consumer Pricing team to tackle complex pricing challenges at Deliveroo. We are advancing towards dynamic, personalized pricing strategies that take into account consumer behavior, loyalty programs, and real-time market conditions.Your daily tasks will include:Designing and developing high-performance machine learning and optimization systems that guide Deliveroo’s core decisions at scale.Leading the technical advancement of our pricing infrastructure, resolving architectural bottlenecks and integrating enhanced model inputs and decision variables.Creating algorithms to enhance real-time marketplace efficiency, including personalized elasticity models and delivery time forecasts.Collaborating closely with Product Managers and Data Scientists to convert complex business challenges into effective algorithmic solutions.Providing technical leadership across various product domains, identifying and prioritizing high-impact algorithmic enhancements.Mentoring and guiding fellow engineers, elevating technical standards and advancing our machine learning and optimization practices across the company.Qualifications for SuccessThe ideal candidate will possess strong expertise in several of the following areas, along with a desire to grow in others: