Remote Senior Machine Learning Engineer

Description:

• Freenome is seeking a Senior Machine Learning Research Engineer to join the Machine Learning Science (MLS) team within the Computational Science department.
• The ideal candidate should have strong knowledge in designing and building deep learning (DL) pipelines and expertise in creating reliable, scalable AI/ML systems in a cloud environment.
• The MLS team develops DL models using massive-scale genomic data, which presents significant challenges for current training paradigms.
• The Senior Machine Learning Research Engineer will be responsible for developing and deploying the infrastructure needed to support the development of DL models, enabling distributed DL pipelines, optimizing hardware utilization for efficient training, and performing model optimizations.
• The role involves collaboration with machine learning scientists, computational biologists, and software engineers to accelerate the development of state-of-the-art ML/AI models.
• The position reports to the Director of Machine Learning Science and can be hybrid based in Brisbane, California, or remote.

Requirements:

• A Master's degree or equivalent experience in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, or Software Engineering, with an emphasis on AI/ML theory and/or practical development is required.
• A minimum of 5 years of post-Master's industry experience in developing AI/ML software engineering pipelines is necessary.
• Proficiency in a general-purpose programming language such as Python (preferred), Java, Julia, C, or C++ is required.
• Strong knowledge of ML and DL fundamentals and hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, Jax, or Scikit-learn is essential.
• In-depth knowledge of scalable and distributed computing platforms that support complex model training, such as Ray or DeepSpeed, is required.
• Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and managing AI/ML models and pipelines in a cloud environment is necessary.
• Understanding of containerization technologies (e.g., Docker) and computing resource orchestration tools (e.g., Kubernetes) is required.
• Proven track record of developing and optimizing workflows for training DL models or large language models (LLMs) is necessary.
• Experience managing large datasets, including data storage and efficient data processing techniques, is required.
• Proficiency in version control systems (e.g., Git) and CI/CD practices is necessary.
• Expertise in building and launching large-scale ML frameworks in a scientific environment is required.
• Excellent ability to work effectively with cross-functional teams and communicate across disciplines is essential.

Benefits:

• The US target range for the base salary for new hires is $161,925 - $247,000.
• Employees will be eligible to receive pre-IPO equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.
• Individual total compensation will be determined at the company’s discretion and may vary based on factors such as location, skill level, years and depth of relevant experience, and education.
• Freenome is an equal-opportunity employer and values diversity, ensuring no discrimination based on various protected statuses.