Lead Machine Learning Engineer
Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic and more than 250 full-time employees) Fusemachines seeks to bring its global expertise in AI to transform companies around the world.
About the role
This is a remote, consulting position
- As a Machine Learning Engineer, you will work at the intersection of machine learning and engineering (i.e., MLOps) to contribute to innovative digital solutions leveraging Surgical ML/AI technologies. Immediate projects and responsibilities may include:
- Integrating machine learning into digital products and services by working cross-functionally across engineering, data science, and machine learning teams
- Developing automated workflows and tools to curate datasets and facilitate training of deep learning models
- Working closely with Machine Learning and Data/Software Engineering teams to develop processes for model deployment/monitoring for various applications.
- Improving and evolving frameworks to manage the lifecycle of model development from research to production to monitoring to continuous improvement
Requirements for the role
- Bachelor’s degree or MS in Computer Science or related technical area with preferably 5-6 years of relevant industry experience developing productionized code in machine learning, data engineering, or related field
- Excellent communication skills both written and verbal
- A desire to work in a high-energy, focused, small-team environment with a sense of shared responsibility and shared reward
- Interest in early research and development through to product roll-out in the fields of surgical AI and surgical robotics
- Hands-on experience with ML frameworks, such as PyTorch, Tensorflow, or similar
- Knowledgeable about MLOps platforms and/or ML CI/CD workflows to manage datasets and model training, deployment, and monitoring
- Experience with Python and SQL
- Experience with cloud compute environments such as AWS, GCP
Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.