Job Description

DESCRIPTION

Job summary
The AWS Ground Truth HIL Data Operation Team is innovating new ways of building massively scalable distributed systems and delivering the next generation of cloud computing with AWS offerings like Polly, SageMaker, and Rekognition

Key job responsibilities
System Development engineers troubleshoot, debug, evaluate and resolve computer-identified alarms, make feature enhancements, bug fixes, systems management, perform software deployments and migrations, host management and automate routine operational tasks. The position requires a combination of strong troubleshooting, technical and communication skills and includes a mix of on call and operational tasks and involves small to medium level software development work. Responsible to develop tools and automations to achieve human free operations. They use the right tool for the job, and modify software in a way that leverages the overall system architecture.
This position is perfect for you if you're interested in creating tools and automation so that engineers can be as hands-off as possible. We want our service to be as autonomous as possible, and that can only be done by having bright engineers who understand how to Think Big, simplify solutions to complex unprecedented problems, all in pursuit of the best customer experience possible. Our environment is built for engineers who flourish in creating automation to reduce the operational workload rather than simply performing operational work all day.

A day in the life
On a "typical" day, System development engineers may work with operations program managers to better understand the use cases of a labeling job, verify the accuracy of labeling job configurations, write and tweak HTML/JS-based graphical user interfaces, deploy labeling jobs, write, tweak, and run pre and post processing code with Python, deliver results to the customer in the format and timeframe they have requested, and troubleshoot, optimize, and document the systems in between.

About the team
Human in Loop service (Sagemaker Ground Truth and A2I) leverages machine and humans to enable customers to create good quality training data which are used to train machine learning models. The quality of model and the inferences in production is driven by the accuracy and quality of the human annotations across all modalities - Text, documents, 2D images, Video and 3D point cloud across mapping, autonomous vehicle, computer vision and NLP domains.

BASIC QUALIFICATIONS

• 4+ years within specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics)
• Minimum 3 years of technical support and/or systems/solutions engineering, and/or development experience
• Minimum 3 years of experience with HTML and Javascript.
• Minimum 3 years experience with Python, Pip, and Virtual Python Environments
• Minimum 3 years experience with Python Boto3 Library, and AWS APIs
• Ability to run and debug code through an IDE such as PyCharm or VSCode
• Minimum 3 years of experience with Linux OS, shell scripting and shell commands
• Minimum 3 years of experience with Git
• Minimum 3 years of experience with AWS Cloud Services, with intermediate to expert level familiarity with: Lambda, S3, EC2, IAM, Sagemaker Ground Truth, Amazon A2i, CloudWatch Events, CloudWatch Logs
• Proven experience designing, building and maintaining high volume and low latency mission-critical systems

• Ability to showcase/demo/walk-through existing Python code you've written
• Ability to see opportunities for improvement, take ownership and closely work with development team to drive product improvement.
• Knowledge of SQL/NoSQL via experience with DBs like MySQL, MongoDB
• Familiarity with machine learning concepts, specifically the labeling stage
• Familiarity with Amazon CDK for Python
• B.S. or M.S. degree in Computer Science, Engineering, Information Systems, or a related field (or equal experience)