Machine Learning Engineer

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
• Working 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 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.