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 clients.
- Qualifications: Experience with cloud services and data technologies; creativity and quick learning are key.
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 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
✨Tip Number 1
Network like a pro! Reach out to folks in the ML Engineering space on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving cloud platforms and data pipelines. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your ML concepts and coding skills. Practice common interview questions and maybe even do mock interviews with friends or mentors.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your hands-on experience with cloud services and data technologies, as these are key for the Machine Learning Engineer role.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about ML Engineering. Share specific examples of projects you've worked on that demonstrate your ability to solve complex problems and work in a multi-disciplinary team.
Showcase Your Technical Skills:Don’t shy away from listing your technical proficiencies! Whether it’s your experience with DevOps tools or your knowledge of scalable data pipelines, make sure we see what you bring to the table.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Accenture
✨Know Your Tech Stack
Make sure you’re well-versed in the cloud services and data technologies mentioned in the job description. Brush up on AWS, GCP, Azure, and big data platforms like Hadoop and Spark. Being able to discuss your hands-on experience with these tools will show that you’re ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex ML engineering problems. Think about challenges you've faced in previous roles and how you creatively solved them. This will demonstrate your ability to think critically and drive solutions, which is key for this role.
✨Collaborate Like a Pro
Since the role involves working closely with various teams, be ready to talk about your experience in multi-disciplinary environments. Share stories of how you’ve enabled others and contributed as a technical expert. This will highlight your teamwork skills and adaptability.
✨Stay Curious and Eager to Learn
Accenture values professionals who are willing to learn quickly. Be prepared to discuss how you keep up with industry trends and new technologies. Mention any recent courses or certifications you’ve pursued, as this shows your commitment to continuous improvement.
