Machine Learning Engineer

Key Skills

Java Programming, building projects, Python Programming, SQL, AWS, Apache Hadoop, Apache Kafka, Scala Programming, Machine learning techniques, Deep Learning, NoSQL, PyTorch, TensorFlow, GraphQL, GPUs, MxNet, SPARK Programming

Job Description

Job summary

Excited by using massive amounts of data to develop Machine Learning (ML) and Deep Learning (DL) models? Want to help public sector, medical center, and non-profit customers derive business value through the adoption of Artificial Intelligence (AI)? Eager to learn from many different enterprise’s use cases of AWS ML and DL? Thrilled to be key part of Amazon, who has been investing in Machine Learning for decades, pioneering and shaping the world’s AI technology?

At Amazon Web Services (AWS), we are helping large 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.

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. 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.

As a machine learning engineer, you will get to work with an innovative company, with great teammates, and have a lot of fun helping our customers. A successful candidate will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term solutions.

Major responsibilities include:

• Understand the customer’s business need and guide them to a solution using our AWS AI Services, AWS AI Platforms, AWS AI Frameworks, and AWS AI EC2 Instances .
• Provide expertise in the development of ETL solutions on AWS
• Assist customers by being able to deliver a 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 Deep Learning frameworks like PyTorch, Tensorflow and MxNet to help our customers build DL models.
• Work with our Professional Services Big Data consultants to analyze, extract, normalize, and label relevant data.
• Work with our Professional Services DevOps consultants to help our customers operationalize models after they are built.
• Assist customers with identifying model drift and retraining models.
• Research and implement novel ML and DL approaches.

BASIC QUALIFICATIONS

• BS or Masters degrees in computer science, engineering, or related technical, math, or scientific field
• 7+ years of professional experience in a business environment
• 7+ years of experience of IT platform implementation in a highly technical or analytical role
• 3+ years of experience handling large datasets
• 3+ years Application Development experience required with cloud technologies
• 3+ years of experience with database flavors of RBDMS, NoSQL, Graph, or Search
• Strong understanding of DevOps practices with practical hands-on application
• Strong understanding of code management and code deployment
• Proficiency developing software code in one or more programming languages (Java, Scala, Python, etc.)
• Strong interest in Machine Learning solutions
• Strong verbal and written communications skills and ability to lead effectively across organizations

PREFERRED QUALIFICATIONS

• 2+ years of relevant experience in building large scale machine learning or deep learning models and/or systems
• 3+ years of hands-on experience in implementation of Big Data systems like Hadoop/Spark clusters
• 3+ years Application Development experience required with serverless technologies
• 2+ years IoT hands-on implementation experience (edge computing preferred)
• 2+ years of experience with Streaming technologies (Kafka, Kinesis, etc.)
• 3+ years working with enterprise customers
• AWS DevOps Professional, Developer Associate, or Ops Associate certification
• 1+ years hands-on experience with MXNet, TensorFlow, or PyTorch
• Experience training distributed ML models on CPU and GPU hardware
• Serving ML models through realtime APIs
• Experience deploying production-grade machine learning solutions on public cloud platforms