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?
Excited by using massive amounts of data to develop Machine Learning (ML) and Deep Learning (DL) models?
Want to help the largest global enterprises derive business value through the adoption of Artificial Intelligence (AI)?
Thrilled to be a key part of Amazon, who has been investing in Machine Learning for decades, pioneering and shaping the world's AI technology?
Machine learning (ML) has been strategic to Amazon from the early years.
We are pioneers in areas such as recommendation engines, product search, e Commerce fraud detection, and large-scale optimization of fulfillment center operations.
At Amazon Web Services (AWS), we are helping enterprises build ML and DL models on the AWS Cloud.
We are applying predictive technology to large volumes of data and against a wide spectrum of problems.
Our Professional Services organization works together with our AWS customers to address their business needs using 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 make plans for launching solutions at scale.
The AWS Professional Services team provides guidance on 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.
If you have experience with AI, including building ML or DL models, we'd like to have you join our team.
You will get to work with an innovative company, with great teammates, and have a lot of fun helping our customers.
Key job responsibilities A successful candidate will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term solutions.
It will be a person who likes to have fun, loves to learn, and wants to innovate in the world of AI.
Major responsibilities include: Interact with customers directly to understand the business problem, help and aid them in the implementation of AI solutions, deliver briefings and deep dive sessions to customers and guide customers on adoption patterns and paths to production.
Understand the customer's business need and guide them to a solution using our AWS AI Services, AWS AI Platforms, and AWS AI Frameworks.
Assist customers by being able to deliver an ML / DL project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models to deliver business impact to the organization.
Use Amazon Sage Maker and Amazon Bedrock to help our customers build AI and ML models.
Assist customers with identifying model drift and retraining models.
Research and implement novel ML and DL approaches.
Deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholders.
About the team 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 the 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.
AWS Professional Services is a unique consulting team.
We pride ourselves on being customer-obsessed and highly focused on the AI enablement of our customers.
Here at Professional Services, we engage in a wide variety of business-critical and global scale projects for customers and partners and help them best utilize the ever-evolving AWS platform.
Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based on customer needs.
About AWS AWS values diverse experiences.
Even if you do not meet all of the 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.
Here at AWS, it's in our nature to learn and be curious.
Our employee-led affinity groups foster a culture of inclusion that empowers us to be proud of our differences.
Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and Amaze Con (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
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 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.
- Knowledge of the primary AWS services (EC2, ELB, RDS, Route53 & S3) - Experience implementing AWS services in a variety of distributed computing environments - 3+ years of experience building models for business applications - Bachelor's degree and 5 years of experience or Master's degree and 2 years of experience - 5+ years of IT implementation experience - Graduate degree (MS or Ph D) 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 Sage Maker, EMR, S3, Dynamo DB, and EC2 - Experiences related to machine learning, deep learning, NLP, CV, GNN, or distributed training - Hands-on experience building models with deep learning frameworks like Py Torch, Tensor Flow, or JAX #J-18808-Ljbffr
