Senior Machine Learning Scientist

at  Synthesis Health

WHO WE ARE

We’re a mission and values driven company with tremendous dedication to our customers. Our 100% remote team, spread across the US and Canada, is dedicated to a common goal – to revolutionize healthcare through innovation, collaboration, and commitment to our core values and behaviors.

ABOUT THE OPPORTUNITY

Synthesis Health is looking for a stellar Senior Machine Learning Scientist who enjoys tackling complex technical problems and building innovative solutions that make a real-world impact. You’ll leverage your expertise in machine learning to design, develop, and implement cutting-edge models and algorithms, stay at the forefront of the field by researching new techniques, prepare and analyze massive datasets, train, evaluate, and optimize models for accuracy and generalizability, collaborate across teams to integrate ML solutions, monitor deployed models, and communicate complex technical concepts to both technical and non-technical audiences.

RESEARCH AND KNOWLEDGE MANAGEMENT

• Participates in literature reviews to find state of the art methods for resolving a particular task.
• Presents findings during team meetings. Integrates research findings to solve model development issues.
• Remains up to date on innovations in machine learning.
• Guides the junior members and drives the review process.
• Leads the review process.
• Prepares research and findings for publications, patents and/or regulatory submissions.
• Presents the findings internally and externally.

QUALIFICATIONS

• Master’s degree or above in computer science, engineering, mathematics, or statistics (preferably with a specialization in machine learning/computer vision) with a strong understanding and proven experience in data science and machine learning algorithms and tools (e.g., statistics, machine learning, deep learning, and LLM technologies).
• 4+ years of experience in designing, developing, and deploying machine learning models to solve real-world problems. Proven ability to take projects from concept to production, ensuring successful integration and ongoing effectiveness.
• Applied knowledge of software and algorithm design, data structures, complexity analysis, and high-performance computing.
• Experience with deep learning architectures, particularly transformers (e.g., using frameworks like Hugging Face) for natural language processing (NLP) tasks.
• Experienced with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Expert-level proficiency in Python, with experience in utilizing other modern programming languages for machine learning tasks.
• Exposure to and practical experience in applying LLMs like GPT and Gemini, including understanding their capabilities and limitations.
• Deep understanding of how to implement solutions using RAG architecture, including retrieval methods and integration with LLMs.
• Experienced with Git and related source control concepts.

PREFERRED QUALIFICATIONS

• Ph.D in computer science, mathematics, engineering, or statistics (with a specialization in machine learning/computer vision).
• 5+ years of experience in designing, developing, and deploying machine learning models to solve real-world problems. Proven ability to take projects from concept to production, ensuring successful integration and ongoing effectiveness.