Senior Machine Learning Engineer

Senior Machine Learning Engineer

Requirements

• Ph.D. in Statistics, Computational Biology, Computer Science, or related quantitative field as outlined in the essential duties, or master’s degree in Statistics, Computational Biology, Computer Science, or related quantitative field as outlined in the essential duties plus 4 years of experience in lieu of a Ph.D.
• 3+ years of experience in statistics, computational biology, applied mathematics, or related quantitative field as outlined in the essential duties.
• 3+ years of experience with artificial intelligence and machine learning algorithms.
• Demonstrated knowledge and experience with advanced AI concepts, such as artificial neural networks, deep learning, and reinforcement learning.
• Demonstrated knowledge and experience using artificial intelligence and machine learning techniques within one or more of the following fields: natural language processing, image processing and computer vision, image and pattern recognition.
• Demonstrated knowledge and experience with large language models for generative AI and associated concepts, such as transformer architecture and retrieval augmented generation.
• Strong programming ability with demonstrated experience in Python and one or more associated machine learning frameworks, such as TensorFlow, PyTorch, or SKLearn.
• Knowledge of and experience working with open-source AI models.
• Demonstrated ability to perform the essential duties of the position with or without accommodation.
• Authorization to work in the United States without sponsorship.

Responsibilities

• Maintain deep expertise in one or more AI technology areas. Clearly present and communicate relevance of technological advances as relevant to our work in biostatistics, bioinformatics and data science at Exact Sciences.
• Develop perspectives on ‘AI technology affordance’: what do these advances in AI technology allow us to do (more efficiently and / or more effectively) that we couldn’t do before.
• Work with stakeholders to discover and refine requirements for ML- and AI-based solutions to business problems with a focus on bioinformatics, biostatistics and data engineering applications.
• Collaborate with other ML/AI engineers and relevant partners to design software solutions that utilize state-of-the-art artificial intelligence and machine learning techniques.
• Work with other AI and ML engineers and software engineers to implement and deploy ML and AI solutions.
• Work in an Agile framework focused on iterative, rapid delivery of proof-of-concept solutions.
• Contribute to the development of an AI strategy at Exact Sciences that empowers the team to leverage both existing AI and ML tools and those developed in-house to accelerate and enhance bioinformatics, biostatistics and data science processes and outcomes.
• Contribute to internal initiatives to build training resources, develop knowledge bases, and educate on advanced AI and ML technologies and best practices for leveraging them.
• Provide mentorship and coaching to more junior level team members.
• Act as resource and subject matter expert in core team and/or cross-functional meetings.
• Exercise discretion and judgment within broadly defined practices and policies in selecting methods and techniques and evaluation criteria for obtaining and interpreting results.
• Ability to apply strong communication skills and to explain difficult, sensitive, and/or complex information to audiences of peers.
• Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork.
• Support and comply with the company’s Quality Management System policies and procedures.
• Maintain regular and reliable attendance.
• Ability to act with an inclusion mindset and model these behaviors for the organization.
• Ability to work designated schedule.
• Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 85% of a typical working day.
• Ability to travel 5% of working time away from work location, may include overnight/weekend travel.

Preferred Qualifications

• 2+ years of life sciences industry experience working with biological data.
• 2+ years of industry experience in molecular diagnostics, preferably cancer diagnostics.
• Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data.
• Basic knowledge of ML-Ops and processes for managing the versioning and deployment of machine learning models.
• Scientific understanding of cancer biology.