Senior AI/ML Engineer for Production AI Delivery

Deloitte Careers and Employment

United States

Hybrid

USD 87,000 - 134,000

Full time

2 days ago

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Benefits offered by this job

Hybrid working policy

Career development opportunities

Job summary

Deloitte UK is seeking an AI/ML Engineer to join the AI Scaling and Transformation team. You will design, develop and deploy data and AI solutions for clients, combining strong technical capability with client-facing delivery to translate business needs into production-ready systems.

Based in one of our UK offices with hybrid working, you will collaborate with data scientists, engineers and business stakeholders, apply responsible AI practices, and help scale AI initiatives from experimentation

Qualifications

Degree or equivalent in Computer Science, Data Engineering, Mathematics, Artificial Intelligence, Machine Learning or a related discipline.
Hands-on experience designing, developing and deploying AI, ML or Generative AI solutions in a consulting, commercial or technology delivery environment.
Experience working with business and technical stakeholders to understand requirements, shape solution options and deliver measurable outcomes.
Proven ability to own technical deliverables or workstreams, manage delivery priorities and communicate progress clearly to project teams and stakeholders.
Experience working in data-intensive, regulated or complex enterprise environments is advantageous.

Responsibilities

Work with client stakeholders, product owners and Deloitte teams to understand business challenges and translate them into practical AI/ML solution designs.
Design, build, test and deploy machine learning models, Generative AI components, data pipelines and analytics solutions that are robust, scalable and maintainable.
Take ownership of technical deliverables or workstreams, ensuring engineering outputs are aligned to agreed requirements, delivery plans and quality standards.
Support the deployment and operationalisation of AI systems, including model monitoring, performance optimisation, CI/CD and MLOps practices.
Collaborate with solution architects, data scientists, business analysts and engineers to ensure AI solutions are integrated effectively into wider technology and business environments.
Apply responsible AI, security, privacy and governance considerations throughout the development lifecycle.
Contribute to the development of junior team members by sharing engineering knowledge, reviewing outputs and supporting a culture of continuous improvement.