Job ID: 2874530 | AWS EMEA SARL (UK Branch)
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? Machine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations. The AWS Industries Team at AWS helps AWS customers implement Generative AI solutions and realize transformational business opportunities for AWS customers in the most strategic industry verticals. This is a team of architects, data scientists, and engineers working step-by-step with customers to build bespoke solutions that harness the power of generative AI.
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and build applications to launch these solutions at scale. The AWS Industries team provides guidance and implements best practices for applying generative AI responsibly and cost efficiently.
You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
We’re looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the-art solutions for never-before-solved problems.
Key job responsibilities
The primary responsibilities of this role are to:
- Design, develop, and evaluate innovative ML models to solve diverse challenges and opportunities across industries.
- Interact with customers directly to understand their business problems, and lead them by prescriptively defining and implementing scalable Generative AI solutions to solve them.
- Work closely with account teams, research scientist teams, and product engineering teams to design architectures and applications, drive model implementations, and guide new solution deployment.
BASIC QUALIFICATIONS
- Bachelor's degree in computer science, engineering, mathematics or equivalent.
- Experience in software development with object-oriented language.
- Experience in cloud-based solution (AWS or equivalent), system, network and operating system.
- Experience in database (e.g., SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis) and experience hosting and deploying ML solutions (e.g., for training, fine-tuning, and inferences).
PREFERRED QUALIFICATIONS
- Masters or PhD degree in computer science, or related technical, math, or scientific field.
- Strong working knowledge of deep learning, machine learning and statistics.
- Experiences related to AWS services such as SageMaker, Bedrock, EMR, S3, OpenSearch Service, Step Functions, Lambda, and EC2.
- Hands-on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer), machine learning, CV, GNN, or distributed training and strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts.
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 (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Posted:October 17, 2024 (Updated 3 days ago)
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