Manager, AI Engineer, AI & Data, AI Scaling & Transformation

As a practitioner in AI&D, you are responsible for delivering AI/ML Engineering on client projects. You are encouraged to devise innovative solutions to help our clients address their biggest data challenges including developing modern analytics platforms.

AI/ML Engineers develop, deploy, and maintain AI/ML systems. They leverage ML algorithms and deep learning techniques to build models that solve business problems, using data pipelines and cloud infrastructure. They also monitor and optimise model performance.

In your role, you will have responsibility for deliverables and client stakeholder relationships and will be delivering solutions for our clients using agile methodologies. You will often be working in multi-disciplinary teams across a range of industries, subject matters and locations.

Our projects vary greatly and your responsibility as a Manager will differ based on the focus of the client engagement and your skillset, but could include and may require you to:

• Collaborate with client stakeholders and internal teams to understand business requirements and translate them into robust AI solutions.
• Design, develop, and implement end-to-end AI pipelines, including data acquisition, pre-processing, feature engineering, model training, evaluation, and deployment.
• Develop and implement AI/machine learning models where appropriate, supporting use cases such as prediction, classification, automation, and insight generation.
• Design, build, and maintain scalable data pipelines, datasets, and data models to support analytics, reporting, and AI use cases.
• Stay abreast of the latest advancements and trends in AI, continuously exploring and evaluating new technologies and approaches.
• Optimise data processing, storage, and model performance for scalability and efficiency.

Candidates must have experience in AI/ML Engineering involving some or all of the following areas:

• Hands-on experience in developing and deploying AI solutions in a professional setting.
• Experience building data pipelines and working with structured and unstructured data.
• Experience with MLOps tools and best practices for model deployment, monitoring, and governance.
• Experience working in Agile delivery environments.
• Strong analytical and problem-solving skills, with attention to detail.
• Programming: Strong programming skills in Python, SQL, and/or similar languages.
• AI/ML Frameworks: Proven experience with popular AI/ML libraries such as TensorFlow, PyTorch, scikit-learn. Familiarity with Generative AI and/or machine learning frameworks (e.g., Langchain) is desirable.
• ML Algorithms: Strong understanding of machine learning algorithms, deep learning architectures, and statistical modelling techniques.
• Cloud Platforms: Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and their AI/ML services.
• Data Engineering: Proficiency in data manipulation and analysis using SQL and big data technologies (e.g., Spark, Hadoop). Experience with ETL, data pipelines, and automated workflows for moving and processing data.
• Data Governance: Adherence to data governance, security, and privacy standards throughout the development lifecycle, including metadata management, data quality, and lineage tracking.
• Distributed Computing: Knowledge of distributed computing techniques like parallel processing, streaming, and batch workflow orchestration.

Deloitte drives progress. Our firms around the world help our clients become market leaders wherever they compete. Deloitte invests in outstanding people with diverse talents and backgrounds, empowering them to achieve more than they can elsewhere. Our work combines consulting with action and integrity. We believe that when our clients and society are stronger, so are we.