Overview
Hybrid
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - 12 Month(s)
Skills
Amazon Web Services
Amazon SageMaker
Apache Kafka
Django
Python
TensorFlow
Machine Learning Operations (ML Ops)
PyTorch
Scrum
Dynatrace
Flask
Job Details
What your background looks like:
- BS in Computer Science or related fields; MS preferred
- 8+ years experience in key engineering roles, such as technical lead, software engineer, and software architect.
- 5+ years experience using Amazon Web Services (AWS) to architect and deploy reliable, cost-effective, scalable, and secure cloud native solutions. Experience working in an agile / scrum environment
- Deep understanding of cloud computing technologies and workload transition challenges, knowledge of AWS Well-Architected Framework, industry standards, and best practices
- Strong experience with MLOps platforms such as AWS Sagemaker, Kubeflow, or MLflow.
- Hands-on design and development experience using Python, Flask, Django, AsyncIO, etc.
- Good understanding of distributed software applications, including system integration, testing, and troubleshooting
- Experience in monitoring the health of distributed systems and a strategy for error detection and recovery
- Systems integration experience, including design and development of APIs, Real-Time Systems, and Microservices
- Current cloud technology experience, preferably AWS (EKS, S3, RDS, Lambda, Aurora, ECS-Fargate ...etc.)
- Passionate to learn new frameworks, building new processes and procedures from scratch, and training the analysts on best practices.
- Demonstrable familiarity with CI/CD process, testing frameworks, and practices (CodeCommit, CodeDeploy, CodePipeline, Jenkins, Harness, etc.)
- Experience integrating with async messaging, logging, or queues, such as Kafka, RabbitMQ, or SQS.
- Strong knowledge of software development process and project management methodologies.
- Strong problem-solving and analytical skills.
- Excellent communication and documentation skills with the ability to lead cross-functional initiatives.
- Enjoy working in a dynamic, fast-moving, and challenging environment
- Good team player and work with globally distributed teams.
Nice to have
- Experience with monitoring and logging tools - Dynatrace, Splunk etc.
- Experience with ML frameworks: TensorFlow, PyTorch, scikit-learn.
- Experience with Kubeflow, MLflow, Airflow, or similar workflow orchestration tools.
- Building automated and scheduled pipelines for analytical processes.
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