Senior AI/ML Software Engineer

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Myriad Genetics

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Molecular Diagnostics • Personalized Medicine • Prognostic Medicine • Companion Diagnostics • Carrier Screen

1001 - 5000

Description

• Develop and Maintain Software: Design and develop scalable software solutions using Kotlin on the JVM ecosystem. Understanding of data structures, data modeling, and software architecture. • IDE Utilization: Utilize IntelliJ IDEA for efficient coding and debugging practices. • Event-Driven Systems: Implement and maintain distributed systems with Kafka for real-time data processing. • Cloud Services: Develop cloud-native applications leveraging AWS services including Lambda for serverless computing, S3 for storage solutions, Step Functions for workflow automation, Textract for text extraction from documents/images, Comprehend for natural language processing tasks and use of Bedrock for customizing and deploying generative AI models. • Serverless Architecture: Architect serverless applications using the Serverless Framework to manage deployment processes efficiently. • Scripting and Automation: Write robust Python scripts to automate tasks or handle backend logic when necessary. • Machine Learning: Apply basic machine learning principles to enhance product features or optimize processes. Expertise with Language foundation models with specific use cases and familiarity with CI/CD in model lifecycle management. Knowledge of machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn).

Requirements

• Proficiency in Kotlin and Java: Strong understanding of the JVM ecosystem. • Experience with IntelliJ IDEA: Familiarity with IntelliJ IDEA or similar IDEs. • Knowledge of Apache Kafka: Experience building event-driven architectures. • Hands-on Experience with AWS: Proficiency with AWS cloud services mentioned above; certification is a plus. • Serverless Framework: Familiarity with the Serverless Framework or similar infrastructure as code tools. • Python Programming Skills: Strong Python programming skills with an emphasis on writing clean and maintainable code. • Understanding of Machine Learning: Knowledge of machine learning concepts and their application in software development. Experience with data engineering and data science frameworks as well as CI/CD concepts and tools.