At a Glance
- Tasks: Scale ML models, design data pipelines, and deploy innovative client-facing products.
- Company: Join Accenture, a leader in modern data and analytics solutions.
- Benefits: Enjoy 30 days vacation, private medical insurance, and extra leave for charity work.
- Other info: Collaborative environment with extensive training and career growth opportunities.
- Why this job: Be at the forefront of ML Engineering and make a real impact on client solutions.
- Qualifications: Experience in cloud services, data technologies, and a passion for learning.
The predicted salary is between 50000 - 70000 £ per year.
About the Role
ML Engineering at Accenture is at the forefront of driving the vision for modern data and analytics platforms to deliver well architected and engineered data and analytics products leveraging cloud tech stack and third-party products. As one of the newest areas in Accenture's Applied Intelligence community, ML Engineering sits at the cross-section of best practices from DataOps, DevOps and ModelOps combining enthusiasts from a variety of backgrounds. Combining experience in digital asset development and large-scale delivery, as well as ML Engineering subject matter expertise help us to deliver client value quickly and close the loop between ML research and deploying to production. Thanks to our strong client delivery focus, we are always on the search for ground-breaking new products, features and solving problems for our customers and we are looking for similar-minded people to help us accelerate those capabilities.
In this role you will:
- Scale existing ML models into production on a variety of cloud platforms
- Design, develop, test, and deploy data pipelines, machine learning infrastructure and client-facing products and services.
- Provide best-practice knowledge, reference architectures, and patterns for use across ML engineering and architecture communities
- Perform technical architecture assessments, analyse and resolve Analytics/ML related architectural problems
- Work closely with engineering, data science and operations teams to provide improvements and focus areas
Who we are looking for:
We are looking for technical professionals from a variety of backgrounds with the willingness and ability to learn quickly, think creatively and drive complex ML Engineering problems to a solution. We offer extensive opportunities for training and upskilling as part of our technical career track, however, we'd typically expect experience in at least two of the following areas:
- Hands-on experience in development, deployment and operation of data technologies and platforms such as: Cloud Services – AWS, GCP, Azure (and/or others)
- Data platforms – Big Data (e.g. Hadoop, Spark, Hive, Kafka), Data Warehouse (e.g. Teradata, Redshift, BigQuery, Snowflake), batch/streaming/low latency processing
- Platform Engineering – DevOps (Ansible, Jenkins, ELK), Containerisation (Docker, Kubernetes), Integration (APIs, microservices, ETL patterns)
- Experience in designing and managing key elements of a data and ML platforms: scalable data pipelines, feature stores, data warehouse, metadata, data quality, data security and encryption
- Experience in developing and architecting software across the full lifecycle from prototype to production.
- Experience in data and ML strategy, including analytics portfolio management (including experience in FinOps and Cloud operating model), use case design and definition, migration strategy etc
Additionally, we would love to see:
- Evidence of willingness and ability to learn quickly and the ability to apply creative thinking to find solutions and drive them to completion
- References to working in a multi-disciplinary team where you enjoyed being the technical expert and enabling others via collaborating as part of a community
- Business and commercial acumen and/or sales experience
What's In It For You
At Accenture in addition to a competitive basic salary, you will also have an extensive benefits package which includes 30 days' vacation per year, private medical insurance and 3 extra days leave per year for charitable work of your choice!
Flexibility and mobility are required to deliver this role as there will be requirements to spend time onsite with our clients and partners to enable delivery of the first-class services we are known for.
Machine Learning Engineer in London employer: Accenture
Accenture is an exceptional employer for Machine Learning Engineers, offering a dynamic work culture that fosters innovation and collaboration across diverse teams. With extensive training opportunities, a competitive benefits package including 30 days of vacation and private medical insurance, and a commitment to community engagement through additional leave for charitable work, Accenture empowers its employees to grow both personally and professionally while making a meaningful impact in the field of data and analytics.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the ML Engineering space. Attend meetups, webinars, or even just chat with people on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving cloud platforms and data technologies. This is your chance to demonstrate your hands-on experience and creativity in solving complex ML problems.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of data pipelines, ML infrastructure, and cloud services. Practice explaining your thought process and solutions clearly, as communication is key when working in multi-disciplinary teams.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate individuals who want to make an impact in ML Engineering. Your next big opportunity could be just a click away!
We think you need these skills to ace Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight relevant experience in cloud services, data technologies, and any hands-on projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're passionate about ML Engineering and how your background makes you a great fit for our team. Don't forget to mention any creative solutions you've implemented in past roles.
Showcase Your Projects:If you've worked on any cool projects related to ML or data engineering, make sure to include them in your application. We love seeing real-world examples of your work, especially if they demonstrate your ability to scale models or design data pipelines.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you'll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative to connect with us directly!
How to prepare for a job interview at Accenture
✨Know Your Tech Stack
Make sure you’re well-versed in the cloud platforms mentioned in the job description, like AWS, GCP, and Azure. Brush up on your knowledge of data technologies such as Hadoop and Spark, as well as DevOps tools like Docker and Jenkins. Being able to discuss these confidently will show that you’re ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare examples of complex ML Engineering problems you've tackled in the past. Think about how you approached the problem, the solutions you implemented, and the impact it had. This will demonstrate your ability to think creatively and drive solutions, which is key for this role.
✨Understand the Business Context
Familiarise yourself with Accenture’s focus on client delivery and how ML Engineering fits into that. Be ready to discuss how your technical skills can translate into business value. Showing that you understand the commercial side of things will set you apart from other candidates.
✨Emphasise Collaboration
Since the role involves working closely with engineering, data science, and operations teams, be prepared to talk about your experience in multi-disciplinary teams. Highlight instances where you’ve enabled others or contributed to a community, as this aligns with the collaborative spirit they’re looking for.
