Sr AI/ML Software Engineer

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Job Overview

The Senior AI/ML Software Engineer at Myriad Genetics will be primarily responsible for developing advanced machine learning algorithms and artificial intelligence models to drive innovation within our genomic and diagnostic solutions. This role will encompass end-to-end model development, including data preprocessing, feature engineering, model training, and deployment in real-world applications. The ideal candidate will collaborate closely with cross-functional teams to ensure the integration of AI/ML strategies into our products, contributing to the enhancement of patient care through data-driven insights.

Job Responsibilities

• Design and implement scalable AI/ML models to solve complex business challenges in genomics.
• Work on data collection processes and exploratory data analysis to identify trends and patterns.
• Collaborate with data engineers and scientists to streamline model production and enhance performance.
• Conduct regular testing and validation of algorithms to ensure accuracy and reliability.
• Build and maintain robust codebases using best practices in software development and documentation.
• Present findings and model results to both technical and non-technical stakeholders.
• Stay abreast of emerging technologies and trends in AI and machine learning.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Mathematics, or a related field (Master’s preferred).
• 5+ years of professional experience in software development with a focus on AI/ML applications.
• Strong proficiency in programming languages such as Python, R, or Java.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Solid understanding of algorithms, statistical modeling, and data mining techniques.
• Proven experience working with large datasets and data wrangling tools.
• Excellent problem-solving skills and ability to work in an agile environment.

Technologies & Tools

The Senior AI/ML Software Engineer will utilize a range of technologies including Python, R, TensorFlow, PyTorch, and Scikit-learn, along with data processing tools such as Pandas and NumPy. Familiarity with cloud platforms (AWS, Azure, or Google Cloud) for deploying machine learning models is also essential. The role requires hands-on experience with version control systems like Git and knowledge of containerization tools like Docker for application deployment and scalability.

Ideal Candidates

Ideal candidates for this position will possess a strong analytical mindset, excellent communication skills, and the ability to work collaboratively within a team-oriented setting. They should exhibit a passion for leveraging AI and machine learning to create impactful solutions in the healthcare domain. The ability to adapt to rapidly changing technologies and a proactive approach to problem-solving will also be key to success in this role. Candidates must demonstrate a commitment to continuous learning and professional growth.