At a Glance
- Tasks: Lead innovative AI/ML projects and shape technical strategies for enterprise customers.
- Company: Join AWS, the leading cloud platform known for its innovation and inclusivity.
- Benefits: Enjoy flexible work-life balance, mentorship, and career growth opportunities.
- Other info: Diverse team culture that values unique experiences and perspectives.
- Why this job: Make a real impact in AI/ML while working with cutting-edge technologies.
- Qualifications: Experience in AI/ML, cloud solutions, and strong technical leadership skills.
The predicted salary is between 72000 - 88000 £ per year.
As a Senior AI/ML Consultant in AWS Professional Services, you will lead the delivery of cutting-edge artificial intelligence and machine learning solutions for our enterprise customers. You'll drive innovation in Artificial Intelligence and Machine Learning, shape technical strategy, and serve as a trusted advisor to customers throughout their AI transformation journey.
Key job responsibilities:
- Lead end-to-end delivery of complex AI/ML engagements, from strategic planning through to pre-production deployment and optimisation.
- Architect and implement advanced solutions leveraging AWS's AI/ML services, with particular focus on Generative AI using Amazon Bedrock and SageMaker.
- Provide technical leadership and mentorship to junior consultants while driving best practices across delivery teams.
- Partner with customers to translate business challenges into measurable ML 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.
This role will be based in our AWS offices in London, Manchester, Bristol or Cambridge, when not at the Customer site. You will need to be able to obtain and maintain a UK Government Security Clearance.
Basic Qualifications:
- Bachelor's degree, or experience in a professional field or military.
- Experience as technical specialist in design and architecture.
- Experience in database (e.g. SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis).
- Experience in consulting, design and implementation of serverless distributed solutions.
- Experience in software development with object-oriented language.
- Experience in cloud-based solution (AWS or equivalent), system, network and operating system.
- Experience in external or internal customer facing, complex and large scale project management.
- Experience building complex highly-scalable systems that involve predictive models or applications of machine learning.
- Experience in data and machine learning engineering and cloud native technologies.
- Eligibility for the UK Security Clearance.
Preferred Qualifications:
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or PhD.
- Knowledge of the primary AWS services such as EC2, ELB, RDS, VPC, Route53, and S3.
- Experience with software development life cycle (SDLC) and agile/iterative methodologies.
- Experience facilitating discussions with senior leadership regarding technical/architectural trade-offs, best practices, and risk mitigation.
- Experience creating and delivering written and oral communications for technical and non-technical audiences.
- Experience in using Python and hands-on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet.
Senior AI/ML Consultant, AWS Professional Services in Cambridge employer: Amazon
Amazon is an exceptional employer, offering a dynamic internship experience in the vibrant region of Yorkshire and the Humber. With a strong focus on employee growth, interns benefit from hands-on project delivery, collaboration with industry experts, and a clear pathway to graduate opportunities, all within a supportive work culture that values innovation and data-driven decision-making.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI/ML Consultant, AWS Professional Services in Cambridge
✨Join Local Tech Meetups
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We think you need these skills to ace Senior AI/ML Consultant, AWS Professional Services in Cambridge
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Amazon.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Amazon and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Amazon
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Amazon uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
