Machine Learning Software Engineer, Medical Imaging Productionization (REMOTE)

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

Our team is part of the larger Pathology efforts at Alphabet, and we combine the latest in machine learning (ML) research with life sciences domain expertise and Google’s infrastructure to create innovative solutions and bring them to the world. The candidate would be working in collaboration with Google and Verily's research, software engineering, science, clinical, regulatory, and quality teams, and would help develop and productionize models and tools for disease diagnosis and treatment determination.

Responsibilities

• Be part of the product teams translating advanced ML research into innovative digital health and global regulated Software as a Medical Device (SaMD) products. 
• Work as an independent ML software engineer through the entire cycle of SaMD productionisation under regulatory and quality management processes. 
• Collaborate and communicate with a dynamic cross org group of various stakeholders, including machine learning scientists, software engineers, quality engineers, regulatory specialists, clinicians, pathologists, and external partners. 
• Actively participate in scoping requirements, ML software system design and development, ML model development, evaluation, and validation.

Qualifications

Minimum qualifications:

• BA/BS degree in Computer Science, Electrical Engineering, or equivalent practical experience in software engineering.
• 3+ years of machine learning experience, familiarity with machine learning model development lifecycle, including study design, data collection and annotation, model development, model validation, and rigorous statistical analysis. 
• Experience with programming and scientific computation using Python and Tensorflow/PyTorch.

Preferred qualifications:

• Passion in delivering real-world impact in the space of healthcare and technology and a rigorous scientific mindset.
• Excellent communication skills and ability to utilize a collaborative approach to solving challenging problems.
• PhD degree in machine learning, bioinformatics, statistics, applied mathematics or related disciplines, or masters degree in similar fields with 3+ years of industry experience.
• Prior experience with cloud development and deployment technologies such as: Docker, Kubernetes, and Cloud Platforms.
• Publications in premiere, peer-reviewed machine learning, scientific, or clinical venues.