![Fusemachines](https://media.trabajo.org/img/noimg.jpg)
Sr. Machine Learning Engineer
hace 4 días
**About Fusemachines**
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 350+ full-time employees) Fusemachines seeks to bring its global expertise in AI to transform companies around the world.
**About the role**
**Role scope**
- Research, design, and develop machine learning algorithms for computer vision, taking advantage of the unique capabilities of Apple silicon.
- Collaborate with machine learning engineers and to optimize and fine-tune machine learning models for efficient execution on Apple silicon architecture.
- Develop and maintain end-to-end pipelines for data collection, preprocessing, training, and deployment of machine learning models.
- Explore and implement innovative techniques in deep learning, neural networks, and optimization to enhance the performance of computer vision and 3D reconstruction algorithms.
**Requirements for the role**
- Applicants should have a Masters, PhD, or advanced training in applied mathematics, engineering, computer science, or a similar related field.
- 8+ years experience in Data Scientist or Machine learning.
- Strong programming skills in languages such as Python, Swift, C, and C++.
- Hands-on experience with ML frameworks, such as PyTorch, or Tensorflow
- Experience with cloud compute environments such as AWS, GCP, Azure
- Solid understanding of computer vision concepts, 3D geometry, and image processing techniques.
- Familiar with visionOS
- Extensive experience in optimizing machine learning models for specialized hardware architectures, particularly Apple silicon.
- Strong problem-solving skills and attention to detail.
- Excellent communication skills both written and verbal.
- 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._
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