Machine Learning Engineer, ProServe GenAI

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 Generative AI Innovation Center team helps AWS customers accelerate the use of Generative AI to solve business and operational challenges and promote innovation in their organization.

In this role you are passionate, talented, and inventive Machine Learning Engineer with a strong background in ML and AI to help develop solutions by pushing the envelope in Generative AI, Time Series, Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV).

Sales, Marketing and Global Services (SMGS)

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.

The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success.

AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

Key job responsibilities

As a Machine Learning Engineer, you are proficient in developing and deploying advanced ML models to solve diverse challenges and opportunities.

You will be working alongside scientists with terabytes of text, images, and other types of data and develop novel models to solve real-world problems.

You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

You will apply classical ML algorithms and cutting-edge deep learning (DL) approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.

The primary responsibilities of this role are to :

Interact with customer directly to understand their business problems, and help them with defining and implementing scalable ML / DL solutions to solve them

Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new algorithms.

About the team

ABOUT AWS : Diverse Experiences

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.

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.

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 flexible work hours and arrangements are part of our culture.

When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

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.

Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship and 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.

We are open to hiring candidates to work out of one of the following locations :

Arlington, VA, USA Atlanta, GA, USA Boston, MA, USA Houston, TX, USA Jersey City, NJ, USA Miami, FL, USA New York, NY, USA Santa Clara, CA, USA Seattle, WA, USA

BASIC QUALIFICATIONS

• 3+ years of non-internship professional software development experience
• 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience programming with at least one software programming language
• 2+ years of relevant experience in developing and deploying large scale machine learning or deep learning models and / or systems into production, including batch and real-time data processing, model containerization, CI / CD pipelines, API development, model training and productionizing ML models
• Experience using Python and frameworks such as Pytorch, TensorFlow

PREFERRED QUALIFICATIONS

• Graduate degree (MS or PhD) in computer science, engineering, mathematics or related technical / scientific field
• Practical experience in solving complex problems in an applied environment
• Experiences related to AWS services such as SageMaker, EMR, S3, DynamoDB and EC2
• Experiences related to machine learning, deep learning, NLP, CV, GNN, or distributed training
30+ days ago