At a Glance
- Tasks: Lead the development and deployment of cutting-edge ML and AI solutions.
- Company: Join Royal Canin, a leader in pet care innovation and digital transformation.
- Benefits: Competitive salary, bonuses, and top-notch learning opportunities from day one.
- Why this job: Make a real impact by leveraging data to drive innovation and efficiency.
- Qualifications: 5-7 years in a quantitative role with strong ML and AI experience.
- Other info: Collaborative environment focused on growth and customer-centric solutions.
The predicted salary is between 43200 - 72000 Β£ per year.
Royal Canin is undergoing a significant Digital Transformation journey. Our ability to solve the most critical problems across Mars in a User Centric way through Data & Analytics is fundamental to our growth ambition and transformation. Significant early success in this journey, and the introduction of many critical foundational capabilities, means that we are looking to accelerate our ability to solve problems and ultimately drive value for Mars Inc.
The opportunities are significant for Mars, and the opportunities for those working in this space are both hugely exciting and rewarding. Connecting and deriving break-through insight from our Royal Canin and Petcare data ecosystems, leveraging the rapidly growing world of external data to get closer to our customers and consumers than ever before, and unlocking efficiencies and automation across our End-To-End Value Chain.
Building on this momentum, we are recruiting a Machine Learning and AI Engineering Lead to join our Royal Canin Global Data & Analytics Team who will accelerate the shaping and delivery of our Data & Analytics Agenda. The Machine Learning and AI Engineering Lead will oversee ML and GenAI solution development and deployment as a capability served within the Data & Analytics solution portfolio. The role is integral to the organization's mission of leveraging advanced technologies to drive innovation and efficiency across the organisation.
The role is part Engineering and platform organisation and will work closely with the Data Science Lead to develop and execute an AI and ML roadmap aligned with business goals and demand.
Key Responsibilities:
- Serve as the technical lead for Generative AI and machine learning model deployment within RC D&A.
- Collaborate with the Data Science team to design, prototype and build next generation ML and AI products and accelerators.
- Design, architect and review technical architecture for data science, machine learning and AI solutions and provide feedback for optimal implementation.
- Develop and oversee the implementation of an MLOps and LLMOps strategy.
- Review code developed by the data science team to ensure solution can be deployed.
- Identify opportunities to optimize methodologies.
- Contribute to a high performing data science function through coaching data scientists and providing training on writing scalable code and good software engineering practices.
- Create repeatable, interpretable, dynamic and scalable model training pipelines that are incorporated into analytic data products through cloud web applications and APIs.
- Define key performance indicators (KPIs) and implement monitoring systems for deployed products to ensure continuous operational performance.
- Define strategy to handle incident management.
- Engage with Platform Product team to scope, plan and implement accelerators and ML platform components.
- Stay updated with the latest advancements in MLOps and apply relevant techniques into projects.
- Educate D&A on technological advancements in this area.
- Maintain comprehensive documentation for model training pipelines, deployment processes, and code.
- Partner with the Product Management squad model and provide advice on how inflight projects can utilise ML and AI to generate additional value.
What are we looking for?
- 5-7 years of experience working in a quantitative role preferably in the CPG or retail industry.
- Proven track record of delivering value through AI/ML/Data Science products in a fast-paced, agile environment using a scalable and reusable codebase and models to address business problems effectively.
- Partner with business leadership across functions and data science teams to identify business challenges and opportunities and translate them into actionable, integrated, data-driven solutions.
- Eagerness to learn, flexibility to pivot when needed, savviness to navigate and thrive in a dynamic environment, and a growth mindset needed to build a successful team.
- A strong customer centric mindset especially within an internal customer base with the purpose of driving value creation, adoption and use.
- Strategic thinking, problem solving and innovation, with the ability to anticipate and navigate challenges and opportunities.
- Ensure compliance with analytics standards, including tailoring methodologies to specific use case needs such as ML, AI, and descriptive analytics.
- Ability to translate business needs into analytical frameworks & superior verbal and written communication skills.
- Working understanding of ML Ops and DevOps frameworks.
- Familiarity with Microsoft Azure tech stack, including but not limited to AzureML, Azure AI Foundry, Databricks.
What can you expect from Mars?
- Work with diverse and talented Associates, all guided by the Five Principles.
- Join a purpose-driven company where weβre striving to build the world we want tomorrow, today.
- Best-in-class learning and development support from day one, including access to our in-house Mars University.
- An industry-competitive salary and benefits package, including company bonus.
Machine Learning Engineering Lead in Slough employer: Mars, Incorporated
Contact Detail:
Mars, Incorporated Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land Machine Learning Engineering Lead in Slough
β¨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
β¨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects and any relevant work you've done. This is your chance to demonstrate your expertise and passion for AI and ML, so make it shine!
β¨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to ML and AI, and be ready to discuss how you've tackled challenges in past projects.
β¨Tip Number 4
Don't forget to apply through our website! Itβs the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at Royal Canin.
We think you need these skills to ace Machine Learning Engineering Lead in Slough
Some tips for your application π«‘
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience in machine learning and AI. We want to see how your skills align with the role, so donβt hold back on showcasing relevant projects or achievements!
Showcase Your Technical Skills: Since this role is all about ML and GenAI, be sure to include specific technologies and frameworks youβve worked with, like AzureML or Databricks. We love seeing hands-on experience, so let us know what you've built and how it made an impact.
Be Clear and Concise: When writing your application, keep it straightforward and to the point. Use clear language to explain your past roles and responsibilities, and make sure we can easily see how you can contribute to our Data & Analytics team.
Apply Through Our Website: We encourage you to submit your application through our website. Itβs the best way for us to receive your details and ensures youβre considered for the role. Plus, itβs super easy to do!
How to prepare for a job interview at Mars, Incorporated
β¨Know Your Tech Inside Out
Make sure youβre well-versed in the latest advancements in machine learning and AI, especially those relevant to MLOps and the Azure tech stack. Brush up on your knowledge of Generative AI and be ready to discuss how youβve applied these technologies in past projects.
β¨Showcase Your Problem-Solving Skills
Prepare examples that highlight your strategic thinking and problem-solving abilities. Think about specific challenges you've faced in previous roles and how you used data-driven solutions to overcome them. This will demonstrate your capability to translate business needs into actionable insights.
β¨Collaboration is Key
Since the role involves working closely with data science teams and business leadership, be ready to discuss your experience in collaborative environments. Share instances where youβve successfully partnered with others to deliver value through AI/ML products.
β¨Prepare for Technical Questions
Expect technical questions related to model deployment, code review, and architecture design. Be prepared to explain your thought process and methodologies clearly. Practising coding problems or discussing your approach to building scalable model training pipelines can give you an edge.