Machine Learning Engineer with Travel Experience

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...

Role Overview Block, Inc. is hiring a Channel Sales Learning and Experience Designer in London. This position plays a key part in developing and delivering sales training for channel partners. The focus: build learning experiences that strengthen partner sales skills and drive real engagement. What You Will Do Design and implement training programs tailored for channel sales partners Create learning materials that connect with a broad, diverse audience Shape content to help partners grow their sales capabilities Bring a creative approach to making training both effective and memorable

ASOS seeks a Machine Learning Engineer in London to focus on recommendation systems. The main responsibility involves developing and refining models that deliver personalized product suggestions to customers. Key responsibilities Design and implement machine learning models that improve the relevance of product recommendations. Translate data insights into practical updates for recommendation algorithms, working alongside team members. Contribute to projects aimed at enhancing the user experience through smarter, more tailored suggestions. Collaboration This role involves partnering with colleagues in data science and engineering to share expertise and strengthen the performance of ASOS’s recommendation systems.

About SwapSwap serves as the backbone of contemporary agentic commerce, being the only AI-native platform that seamlessly integrates backend operations with an innovative storefront experience.Designed for brands looking to sell anything, anywhere, Swap centralizes global operations, enhances intelligent workflows, and empowers margin-protecting decisions through real-time data and capabilities. Our expansive product range covers cross-border transactions, tax solutions, returns, demand planning, and our state-of-the-art agentic storefront, providing merchants with complete transparency to act confidently.At Swap, we cultivate a culture that prioritizes clarity, creativity, and shared ownership as we transform the landscape of global commerce.About the RoleAs the Lead Machine Learning Engineer focusing on Recommendations, you will be responsible for shaping the intelligence behind the AI Storefront at Swap, determining what products are displayed to each shopper. This position is highly technical and hands-on, merging expertise in recommendation systems, large language models (LLMs), and fashion understanding. You will develop the models and pipelines that drive style-aware product recommendations, outfit generation, and personalized discovery, managing the entire process from research and prototyping to production systems that serve actual customers. Collaboration with our conversational AI layer will be essential, as you will extract insightful preference signals through dialogue and integrate these with traditional e-commerce behavioral data and LLM-based world knowledge to enhance recommendations, particularly addressing cold-start challenges in innovative ways.You will establish high technical standards for ML engineering in the recommendations domain at Swap, playing a pivotal role in the evolution of this team area as we scale.

Join Longshot Systems, where we are at the forefront of developing sophisticated platforms for sports betting analytics and trading.We are in search of talented Machine Learning Researchers to join our quantitative modeling team. This team’s primary objective is to enhance the predictive capabilities of our models using historical event and market data. The quality of our models is paramount, as improvements directly influence our company’s success.In this role, you will design, test, and implement innovative machine learning models using Python, continuously enhancing our existing state-of-the-art solutions. As a small, focused company, we offer you the chance to be involved in every aspect of the R&D process, from high-level design to production implementation.The ideal candidate will possess high creativity and enjoy developing new, innovative approaches to problem-solving, and will have the autonomy to explore the most suitable methods for the challenges at hand. A strong mathematical foundation in machine learning and core statistics is essential. While knowledge of sports betting is not required, experience with modeling sports — particularly in-play football, basketball, or tennis — is advantageous.We embrace a hybrid working model, requiring in-office presence on Thursdays at our London (Farringdon) office, while allowing flexibility for the remainder of the week. Our standard working hours are from 10 am to 6 pm UK time, Monday to Friday, with support for flexible schedules to help our team achieve their goals.Our interview process includes:Introductory call (30 mins) - discussing your background and interestsTechnical interview (60 mins) - focusing on modeling questions and a coding exerciseFull assessment day (10:30 am – 5 pm) - encompassing a comprehensive modeling exercise and team interactions

Join Longshot Systems, where we are pioneering cutting-edge platforms for sports betting analytics and trading.We are looking for enthusiastic Graduate Machine Learning Researchers to become integral members of our quantitative modeling team. This team is dedicated to enhancing the predictive capabilities of our models using historical event data, as the excellence of our models is crucial to our company’s success.In this role, you will be responsible for designing, testing, and implementing innovative machine learning models in Python while continuously refining our existing top-tier solutions. As a small, focused company, Longshot offers you the opportunity to engage deeply in all facets of the R&D process, from high-level design to production implementation, while also learning from experienced industry professionals.The ideal candidate will possess a creative mindset and thrive in generating novel approaches to problem-solving. You will have the autonomy to explore and research the most suitable methods for the challenges presented. A solid mathematical foundation in Machine Learning principles and core statistics is essential, though prior knowledge of sports betting is not a requirement.We embrace a hybrid working model, with in-office work on Thursdays at our London (Farringdon) location and remote work for the remainder of the week. Our regular working hours are from 10 AM to 6 PM UK time, Monday to Friday, with a strong emphasis on flexible working to empower our team to achieve their objectives.Our interview process consists of the following steps:Introductory call (30 mins) - Discuss your background and interestsTechnical interview (60 mins) - Engage in modeling discussions and scenario-based questionsFull assessment day (9:30 AM–5 PM) - Tackle a real modeling challenge utilizing near-production dataQualifications A PhD or research Master’s degree in a quantitative, technical discipline (e.g., Mathematics, Physics, Machine Learning) from a reputable university Proficiency in modeling tabular data using Python Benefits Participation in an uncapped company bonus scheme, typically ranging from 10-20% of salary based on experience 10% matched pension contributions Private healthcare coverage Long-term illness insurance Gym membership Choice of hardware and setup for your development environment

At Longshot Systems, we develop cutting-edge platforms for sports betting analytics and trading.We are currently seeking experienced Machine Learning Engineers to join our modeling engineering team. In this role, you will collaborate closely with our quantitative research teams to transform prototype trading models into robust, production-ready systems. You will be responsible for designing and building the tooling, frameworks, and data engineering necessary to support strategy research and development, while also architecting high-level designs of the strategy software to minimize trading latency and ensure scalability. Our ML stack is primarily Python-based, incorporating modern ML libraries and tools such as Polars, Ray, and Plotly.The ideal candidate will possess a solid software engineering background, with extensive experience in high-performance computing topics such as multi-threading, networking, profiling, and optimization. Proficiency with the NumPy/SciPy stack is essential, along with experience in performance optimization tools like C++ and Numba. Familiarity with common ML algorithms and techniques is advantageous but not mandatory.As a hybrid working company, we require team members to work in our London (Farringdon) office on Thursdays, while offering flexibility for remote work on other days. Our standard working hours are from 10 am to 6 pm UK time, Monday to Friday, but we encourage flexible schedules to help our team meet their objectives.Interview Process:Introductory Call (30 mins) - Discuss your background and interestsFirst Technical Interview (30 mins) - Live code review and pair programmingSecond Technical Interview (60 mins) - In-depth technical questionsFull Assessment Day (10:30 am to 5 pm) - A programming exercise reflective of actual team tasks

About Our Client:Our esteemed client specializes in delivering comprehensive IT services, supporting a workforce of approximately 700 employees across 13 offices located in Europe, the Middle East, and North Africa. English serves as the primary language of communication. Since migrating to Office 365 (O365) in 2017, they have significantly expanded their utilization of the business productivity suite, incorporating a variety of applications including Teams, OneDrive, SharePoint Online, OneNote, Forms, Flow, Power BI, Planner, and PowerApps. Enhanced communication tools such as Skype for Business and Zoom are also utilized to foster better collaboration.Position Overview:We are seeking an enthusiastic ICT Apprentice to join our dynamic IT team. The ideal candidate will start as soon as possible and will be required to work flexibly from Monday to Friday, providing IT support to our UK and European offices during the hours of 8 AM to 6 PM GMT, totaling 35 hours per week.Key Responsibilities: Support the IT team in addressing a wide range of computer issues Install and configure IT systems Diagnose hardware and software faults Resolve technical application problems, both in-person and remotely Develop proficiency in O365 applications and contribute to IT support services Perform Active Directory maintenance and manage Teams administration Create user accounts and reset passwords Assist with ongoing IT projects and equipment setup Address user IT queries and create purchase orders Provide service desk support and ensure cyber awareness Contribute to the laptop replacement program and assist in business system implementations Training Opportunities: Receive a Level 3 ICT qualification Engage in online training through a combination of self-paced eLearning and live classes Enhance your functional skills in English and Mathematics, if necessary Additional Considerations: Our client retains the right to adjust the base location in consultation with employees based on organizational needs Occasional out-of-hours work may be required Qualifications: Essential: GCSE or equivalent in English (Grade A* - C 9/4) Essential: GCSE or equivalent in Mathematics (Grade A* - C 9/4) Ideal Candidate: A motivated individual eager to learn and develop IT skills Excellent communication and problem-solving abilities Ability to work collaboratively within a team environment

Join the Future of AI at GraphcoreAt Graphcore, we're at the forefront of AI computing innovation. Our team, comprised of semiconductor, software, and AI specialists, is dedicated to building a comprehensive AI compute stack—from cutting-edge silicon to high-performance software and robust data center infrastructure. Backed by the SoftBank Group's substantial long-term investment, we are pioneering essential technologies within the burgeoning SoftBank AI ecosystem. As we expand globally, we invite you to collaborate with some of the brightest minds in the industry to tackle complex challenges and shape the future of artificial intelligence.Position OverviewAs a Senior Machine Learning Engineer on our Applied AI team, you will play a pivotal role in enhancing AI technologies by developing and optimizing machine learning models specifically designed for our advanced hardware. Your work will focus on large-scale systems where performance is paramount. Collaborating closely with our Software Development and Research teams, you will help identify innovative opportunities that set Graphcore's technology apart in the competitive landscape. We are looking for engineers with robust technical skills and a keen understanding of implementing AI models at scale, who are eager to make a significant impact in this rapidly evolving sector.About the TeamThe Applied AI team acts as advocates for our customers, ensuring that we stay abreast of the latest AI models, applications, and software to guarantee that Graphcore's technology integrates seamlessly into the AI ecosystem at scale. We develop reference applications, enhance essential software libraries—such as optimizing kernels for our hardware efficiency—and collaborate with our Research team to explore and publish groundbreaking ideas in areas like efficient computation, model scaling, and the distributed training and inference of AI models across various modalities and applications. If you are passionate about advancing the next generation of AI models on state-of-the-art hardware, we would love to connect with you!

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.

FRP Advisory is looking for a Corporate Governance Apprentice to join the Professional Services team in London. This entry-level position offers a chance to build a foundation in corporate governance while working alongside experienced colleagues. Role overview The apprenticeship centers on supporting the governance team with day-to-day tasks. Typical responsibilities include helping with compliance processes, preparing reports, and assisting with stakeholder engagement activities. The role provides practical exposure to the core functions of governance within a professional services environment. Learning and development Apprentices will work closely with seasoned professionals who offer guidance and share their expertise. The position is structured to provide both hands-on experience and insight into the field, helping to build essential skills for a future career in corporate governance. Who this role suits This apprenticeship is designed for motivated individuals eager to start a career in governance. It offers a supportive setting for learning and professional growth, making it well suited to those ready to take the first step in the field.

At Orbital Materials, we harness the power of AI to revolutionize data center hardware, ensuring our products consistently outperform the competition. Our advanced AI simulates materials at the atomic level, allowing us to evaluate millions of hardware configurations in the time it would typically take to assess just hundreds. This innovative approach enables us to discover optimal designs that surpass traditional benchmarks, resulting in hardware specifications that competitors cannot match: 1 MW/rack, PUE As each deployment generates valuable field data, our AI models become increasingly sophisticated. This creates a virtuous cycle where improved models lead to better hardware, which in turn enhances our AI capabilities. We are not merely benefitting from AI advancements; we are actively driving its pace.Our focus on data centers is driven by an urgent market need and demanding specifications. However, the AI-accelerated development processes we've established—spanning materials discovery, hardware design, and manufacturing optimization—are applicable to any complex physical system. Data centers serve as our initial proof point, not the limit of our ambitions.With operations in London, Canada, and the USA, we are assembling teams across various domains including ML research, product development, mechanical engineering, and chemical engineering. If you're eager to work at the intersection of AI and physical sciences, we'd love to hear from you.As a Staff Machine Learning Engineer at Orbital, you will be instrumental in architecting sophisticated AI systems for the multi-scale design of physical technologies. By multi-scale, we mean that we create world-class foundational models capable of simulating everything from the microscopic motion of atoms to the macroscopic flow of liquids in 1GW data centers. You will collaborate across these diverse scales, leveraging the creativity of our scientists and engineers, augmented by premier domain agents.In this pivotal role, you will establish exceptionally high technical standards and lead projects from initial prototypes to full-scale production deployment. We seek individuals who possess a passion for craftsmanship, a commitment to continual learning, and a drive to build scalable systems. Additionally, we value a low-ego mindset and a genuine enthusiasm for leveraging AI to tackle significant global industrial technology challenges.

Join the Anthropic Fellows Program where you will delve into the exciting world of Machine Learning Systems & Performance. This unique opportunity allows you to work alongside some of the brightest minds in AI research and development, tackling complex challenges and contributing to groundbreaking projects that aim to enhance the capabilities of machine learning systems.

ABOUT BIGLIGHTBiglight is a cutting-edge experience design agency that seamlessly integrates customer insights, user experience (UX), and innovative design. Our mission is to empower prominent brands to craft extraordinary customer experiences through ongoing innovation and experimental practices.Our distinctive methodology enables brands to uncover the unmet needs of their customers, transforming how they address these needs through rigorous testing, personalized strategies, and service innovation across all platforms.Why Choose Biglight?At Biglight, we envision your career as an exhilarating journey filled with growth, impact, and creativity. This is your chance to influence the future of user experiences for some of the world’s most renowned brands while defining your own professional path.We pride ourselves on being a people-centric organization that thrives on the expertise and talent of our exceptional team. We seek out top-tier talent from diverse backgrounds, fostering an environment that supports development and collaboration, all while partnering with prestigious brands such as The North Face, Vans, and Marks & Spencer.What Awaits YouEngage in Exciting, Real-World ProjectsCollaborate with clients on a variety of projects, working alongside seasoned team members to enhance your skills in both research and design. From wireframing and usability testing to championing user-centered solutions, you will constantly learn through practical experience.Realize Your IdeasYour contributions at Biglight will yield tangible, measurable results. You’ll play a pivotal role in shaping user experiences that directly influence our clients' success, delivering both creative and strategic solutions.Grow with UsWe are dedicated to helping you refine your skills across diverse methodologies, from user research to experience design. As your confidence grows, you will have the opportunity to lead project segments, facilitate workshops, and collaborate closely with clients.

Join Mustard Systems, where we harness the power of statistical modeling to analyze sports events, enabling accurate predictions of future outcomes. By leveraging our proprietary datasets, sophisticated statistical models, and custom software solutions, we aim to deliver precise forecasts in the world of sports.We prioritize speed and real-world impact over perfection in code. If you are an engineer who excels at rapid problem-solving and thrives in a flexible, outcome-oriented environment, you'll find a home with us.Your Role:Enhance our connections to new liquidity providers using advanced web scraping and reverse engineering techniques.Create and maintain low-latency, real-time data feeds to support trading strategies based on extracted data.Improve system visibility for teams to gain insights into integration challenges and enhancements.Our agile methodology allows us to adapt plans as new information and opportunities arise. Developers play a pivotal role, taking complete ownership of their software from design through development, testing, review, and production support.Key Responsibilities:Design and Implement Impactful Features: Develop features that align with our business objectives, ensuring high-quality code that delivers measurable value.Collaborate on Code Quality: Review and test peer code to uphold functionality, maintainability, performance, and quality standards.Production Support: Take charge of your team’s software in production, ensuring stability and prompt resolution of any issues.Cross-Team Collaboration: Partner with other development teams on cross-functional projects, working alongside traders and quants to devise the best solutions to real business challenges.Participate in Out-of-Hours Support for our Software Systems.Core Technology Stack:Languages: Python (3.10+), JavaScript/TypeScript for frontend tasks, and Go for select infrastructure.Tools: RabbitMQ and Kafka for messaging, PostgreSQL and Redis for data storage.Environment: Linux servers.Observability: OpenTelemetry, Prometheus, Grafana, and Zabbix.Required Qualifications:Solid experience in software development, particularly with Python.A degree in Computer Science or a related quantitative field from a recognized university.Excellent communication skills, enabling you to explain complex technical concepts to both technical and non-technical audiences.Strong decision-making skills, with an ability to make informed trade-offs in implementation and architectural decisions, balancing innovation with practicality.Experience with web scraping and related technologies is essential.

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

INEOS Automotive has built a reputation for direct, practical innovation in the automotive industry. From the initial vision of a no-nonsense 4x4, the company now delivers vehicles like the Grenadier to customers worldwide and is developing the Quartermaster double cab pickup. Partnerships with established industry leaders and a dedicated global team have fueled this progress. The company values determination and a willingness to challenge norms. With a diverse team of around 1,500 people representing 44 nationalities across 10 locations, collaboration and a drive to achieve ambitious goals are central to the culture. Role overview The Marketing Manager for Digital Experience and Customer Experience will shape and execute the global strategy for INEOS Automotive’s digital presence. This role centers on optimizing the website and CRM systems to meet customer expectations, support the consideration process, and drive conversions such as test drive bookings, quote requests, finance inquiries, and dealer contacts. What you will do Develop and refine digital experience strategies that support business growth. Implement and manage global customer experience initiatives. Increase website conversion rates and improve key performance indicators. Track and analyze website health metrics, including SEO, bounce rates, and user engagement. Work closely with agency partners to ensure effective project delivery. Oversee email marketing performance and manage automated messaging within resource limits. Lead digital marketing campaigns and drive lead generation activities. Requirements Experience managing digital website operations, optimization, and development for multiple markets and languages. Strong background in CRM systems, including building automated programs for prospect nurturing and customer retention. Self-driven and proactive, able to move initiatives forward independently. Knowledge of optimizing global, multi-market websites and developing effective content. Proven project management abilities and skill in prioritizing tasks. Comfortable adapting to changing business needs and environments. Excellent communication skills, able to connect technical and non-technical teams. This position is based in London, England, United Kingdom.

At Canva, our mission is to empower individuals to unleash their creativity through design. We are innovating AI technology that not only feels intuitive but also creates meaningful impacts for millions, enabling everyone to design with confidence. We are seeking a Senior Research Scientist passionate about reinforcement learning, agentic systems, and mixture of experts (MoE) models to advance our capabilities in reasoning, tool utilization, latency, and reliability.About the TeamOur team delves into multimodal agentic architectures, establishing robust training and evaluation frameworks. We collaborate closely with product and platform teams to transform groundbreaking research into engaging product features. As a pioneering post-training team, we are dedicated to developing advanced multimodal agentic systems. We cover a wide array of topics, including multimodal modeling, post-training strategies, and agent design.About the RoleIn this role, you will influence research directions and engage in hands-on initiatives across the agent stack—from reward design and policy optimization to planning, memory management, tool orchestration, dataset construction, and the innovation of post-training methodologies. You will create meticulously designed experiments, iterate rapidly, and derive reliable conclusions, all while ensuring that research translates into safe, high-quality product experiences.Key ResponsibilitiesDesign and develop agent systems focused on planning, multimodal tool usage, retrieval, innovative training methods, and modeling experiments for real-world applications in design, vision, and language.Implement scalable post-training and reinforcement learning solutions across distributed systems (using PyTorch), optimizing data loaders, telemetry, and stable training of MoE architectures while ensuring reproducibility.Contribute to the reinforcement learning and agentic systems research agenda that aligns with Canva’s product vision; quickly identify and prioritize high-impact projects.Create reward models and learning loops, including RLHF/RLAIF, preference modeling, DPO/IPO-style objectives, offline/online RL, and curriculum learning.Develop simulation tasks that expose failure modes (planning errors, tool-use weaknesses, hallucinations, unsafe actions) and establish measurable targets for improvement.Lead rigorous evaluations for agents, focusing on task success, reliability, latency, safety, and regression testing. Set up offline suites and conduct online A/B testing; favor straightforward experiments that yield generalizable results.Collaborate closely with product, design, safety, and platform teams to successfully integrate research findings into reliable product features.

Founded in 1971 in Somerset, England, Mulberry has established itself as an iconic British lifestyle brand, celebrated globally for its unparalleled quality and design that embodies the Mulberry Spirit.With sustainability ingrained in our ethos since day one, we are proud to have achieved B Corp Certification in 2024, reflecting our commitment to a purpose-driven approach.While we have transformed into a global brand, our core values remain intact; we prioritize enhancing our impact on both people and the planet. Our team is characterized by honesty, dynamism, and a strong sense of community.If you resonate with these values, we invite you to become part of our team.At Mulberry, our Assistant Managers are known as 'People and Experience Leaders.' This role demands a passion for people, a commitment to delivering exceptional customer experiences, and a willingness to grow both personally and professionally. We encourage you to become an expert in your field and actively contribute to our 'Back to the Mulberry Spirit' strategy.Key Responsibilities:Collaborate with the Store Leader to cultivate an exceptional team:Foster a high-performing team where diversity is celebrated and every member feels valued, respected, and included, championing equity, empathy, and understanding in every interaction.Encourage dynamic discussions, welcoming ideas and diverse perspectives to drive creativity and collaboration.Create a culture that embraces honest feedback, recognizing successes, coaching, and providing challenges for growth.Maintain an unwavering focus on customer satisfaction:Nurture a welcoming and enjoyable atmosphere for customers and team members alike.Commit to delivering engaging and memorable customer experiences in your store, inspiring your team to do the same.Stay culturally attuned to how Mulberry integrates into the broader context of life and art, utilizing this understanding to enhance customer interactions.