AI/ML Consultant, Professional Services Full-time

In this role, 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

Use ML and Generative AI tools, such as Amazon SageMaker and Amazon Bedrock to provide a scalable cloud environment for our customers to label data, build, train, tune and deploy their models

Collaborate with our data scientists to create and fine tune scalable ML and Generative AI solutions for business problems

Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem

Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes

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

About the team

Diverse Experiences

AWS 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.

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 & 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.

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 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.

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.

BASIC QUALIFICATIONS

– Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)

– Experience coding in Python, R, Matlab, Java or other modern programming language

– 1+ year of public cloud computing experience in AWS or other large scale cloud providers

– 4+ years of experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inferences)

PREFERRED QUALIFICATIONS

– 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

– Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts

– 5+ years of database (eg. SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis) experience

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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,200/year in our lowest geographic market up to $204,300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.