Principal Machine Learning Engineer

• Lead the design and development of machine learning models and systems for health and life sciences applications, ensuring scalability and reliability.
• Define technical strategy and architecture for ML pipelines, including data ingestion, feature engineering, model training, evaluation, and deployment.
• Collaborate with interdisciplinary teams (including scientists, researchers, and software engineers) to envision and develop AI-augmented scientific systems.
• Mentor engineers and researchers, promoting best practices in ML development, experimentation, and responsible AI principles.
• Ensure security, privacy, and regulatory compliance across ML workflows and data handling.

• Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C++, C#, Java, JavaScript, or Python

• OR equivalent experience., * Masters in Computer Science or related technical field AND 6+ years technical engineering experience including significant work in machine learning or applied AI
• OR equivalent experience.

• Proven track record of designing and deploying large-scale ML or MLops systems in research or product settings.
• Hands-on experience with large-scale distributed training of ML models.
• Deep expertise in ML algorithms, model optimization, and frameworks (e.g., PyTorch, TensorFlow).
• Experience with one or more of: optimizing data mixes, mid-training, post-training, model merging, or model distillation.
• Familiarity with security and compliance standards for enterprise and health data.
• Demonstrated ability to communicate effectively and solve problems in collaborative, research-driven environment.

#Research #healthfutures #researchsystems

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