Data Scientist, AWS Generative AI Innovation Center ...

Amazon
London
2 days ago
Create job alert

Data Scientist, AWS Generative AI Innovation CenterJob ID: 2816978 | Amazon Web Services EMEA Dubai FZ Branch - Q29Amazon launched the Generative AI Innovation Center (GenAIIC) inJune 2023 to help AWS customers accelerate the use of generative AIto solve business and operational problems and promote innovationin their organization. This is a team of strategists, datascientists, engineers, and solution architects working step-by-stepwith customers to build bespoke solutions that harness the power ofgenerative AI. We’re looking for Data Scientists capable of usinggenerative AI and other techniques to design, evangelize, andimplement state-of-the-art solutions for never-before-solvedproblems. You will work directly with customers and innovate in afast-paced organization that contributes to game-changing projectsand technologies. You will design and run experiments, research newalgorithms, and find new ways of optimizing risk, profitability,and customer experience. Emirati national is required. Key jobresponsibilities As a Data Scientist, you will: 1. Collaborate withAI/ML scientists, engineers, and architects to research, design,develop, and evaluate cutting-edge generative AI algorithms toaddress real-world challenges. 2. Interact with customers directlyto understand the business problem, help them in the implementationof generative AI solutions, deliver briefing and deep dive sessionsto customers, and guide customers on adoption patterns and paths toproduction. 3. Create and deliver best practice recommendations,tutorials, blog posts, sample code, and presentations adapted totechnical, business, and executive stakeholders. 4. Providecustomer and market feedback to Product and Engineering teams tohelp define product direction. About the team The team helpscustomers imagine and scope the use cases that will create thegreatest value for their businesses, select and train or fine-tunethe right models, define paths to navigate technical or businesschallenges, develop proof-of-concepts, and make plans for launchingsolutions at scale. The Generative AI Innovation Center teamprovides guidance on best practices for applying generative AIresponsibly and cost-efficiently. BASIC QUALIFICATIONS - Bachelor'sdegree or Master's degree with several years of experience. -Several years of experience building models for businessapplications. - Experience in any of the following areas:algorithms and data structures, parsing, numerical optimization,data mining, parallel and distributed computing, high-performancecomputing, neural deep learning methods, and/or machine learning. -Experience in using Python and hands-on experience building modelswith deep learning frameworks like TensorFlow, Keras, PyTorch,MXNet. PREFERRED QUALIFICATIONS - PhD or Master's degree incomputer science, engineering, mathematics, operations research, orin a highly quantitative field. - Practical experience in solvingcomplex problems in an applied environment. - Hands-on experiencebuilding models with deep learning frameworks like PyTorch,TensorFlow, or JAX. - Prior experience in training and fine-tuningof Large Language Models (LLMs). - Knowledge of AWS platform andtools. Amazon is committed to a diverse and inclusive workplace.Amazon is an equal opportunity employer and does not discriminateon the basis of race, national origin, gender, gender identity,sexual orientation, protected veteran status, disability, age, orother legally protected status. #J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist

Senior Machine Learning Scientist (UK Remote)

Senior Data Scientist

Data Scientist (GenAI - Customer Identity)

Senior Data Scientist

Machine Learning Specialist

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!