Sr Delivery Consultant (AI/ML), Professional Services Join to apply for the Sr Delivery Consultant (AI/ML), Professional Services role at Amazon Web Services (AWS) Description Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Amazon Web Services Professional Services (ProServe) team at AWS helps AWS customers implement AI/ML, Generative AI solutions and realize transformational business opportunities for AWS customers across industry verticals. In this role, you'll work closely with customers to design, implement, and scale AWS solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the project lifecycle. Key job responsibilities

Lead end-to-end delivery of complex AI/ML engagements, from strategic planning through to pre-production deployment and optimization. Architect and implement advanced solutions leveraging AWS's AI/ML services, with particular focus on using Amazon Bedrock, SageMaker etc. Provide technical leadership and mentorship to other consultants while driving best practices across delivery teams. Partner with customers to translate business challenges into measurable outcomes and clear delivery roadmaps. Drive innovation in applied AI/ML, contributing to methodologies and reusable solutions across the practice. Influence customer AI strategy through technical expertise and industry insights. Lead multi-disciplinary teams and coordinate across stakeholder groups to deliver high-impact AI solutions. Provide thought leadership in internal and external engagements. Support pre-sales activities to provide technical expertise and review project scoping and risks.

A day in the life Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture - Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Mentorship & Career Growth - We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance - We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Basic Qualifications

Strong experience in building large scale machine learning or deep learning models and in Generative AI model development. Experience in data and machine learning engineering and cloud native technologies. Strong experience communicating across technical and non-technical audiences. Strong experience facilitating discussions with senior leadership regarding technical / architectural trade-offs, best practices, and risk mitigation. Master's degree in a quantitative field such as statistics, mathematics, data science, engineering, or computer science. Knowledge of data modelling principles, statistical analysis methodologies, and demonstrated ability to extract meaningful insights from complex, large-scale datasets.

Preferred Qualifications

AWS Associate level certifications (e.g., Machine Learning Specialty, Machine Learning Engineer Associate, Solutions Architect Professional) preferred. Experience with software development life cycle (SDLC) and agile/iterative methodologies. Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet. Knowledge of the primary AWS services (EC2, RDS, Route53 & S3). Experience with automation and scripting (e.g., Terraform, Python). Knowledge of security and compliance standards (e.g., HIPAA, GDPR).

Equal Opportunity Employer Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit the accommodations page for more information. Location: London, England, United Kingdom #J-18808-Ljbffr