Machine Learning Engineer, WWPS ProServe Data and Machine Learning

Description

The Amazon Web Services Professional Services (Pro Serve) team is seeking a skilled Machine Learning Engineer to join our team at Amazon Web Services (AWS). 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? In this role, you'll work directly with customers to design, evangelize, implement, and scale AI/ML solutions that meet their technical requirements and business objectives.

You'll be a key player in driving customer success through their AI transformation journey, providing deep expertise in machine learning, generative AI, and best practices throughout the project lifecycle.

As a Machine Learning Engineer within the AWS Professional Services organization, you will be proficient in architecting complex, scalable, and secure machine learning solutions tailored to meet the specific needs of each customer. You'll help 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, and define paths to navigate technical or business challenges.

Working closely with stakeholders, you'll assess current data infrastructure, develop proof-of-concepts, and propose effective strategies for implementing AI and generative AI solutions  will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

This position requires that the candidate selected must currently possess and maintain an active TS/SCI security clearance with polygraph.

• Design and implement complex, scalable, and secure AI/ML solutions on AWS tailored to customer needs, including selecting and fine-tuning appropriate models for specific use cases.
• Develop and deploy machine learning models and generative AI applications that solve real-world business problems, conduct experiments and optimize for performance at scale.
• Collaborate with customer stakeholders to identify high-value AI/ML use cases, gather requirements, and propose effective strategies for implementing machine learning and generative AI solutions.
• Provide technical guidance on applying AI, machine learning, and generative AI responsibly and cost-efficiently, troubleshoot throughout project delivery and ensure adherence to best practices.
• Act as a trusted advisor to customers on the latest advancements in AI/ML, emerging technologies, and innovative approaches to leveraging diverse data sources for maximum business impact.
• Share knowledge within the organization through mentoring, training, creating reusable AI/ML artifacts, and working with team members to prototype new technologies and evaluate technical feasibility.

Diverse Experiences

Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, 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.

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.

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.

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.

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.

• Bachelor's degree or above in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
• 2+ years of data scientist experience
• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
• 1+ years of working with or evaluating AI systems experience
• Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control…