MONA

Sophisticated, modern and high quality – MONA.

Senior Machine Learning Engineer

Full TimeRemoteTeam 501-1,000Since 1989H1B SponsorCompany SiteLinkedIn

Location

United States

Posted

9 days ago

Salary

Not specified

Bachelor Degree4 yrs expEnglishAWSCloudDockerFlaskGoogle Cloud PlatformPythonPy TorchTensorflow

Job Description

• Design and implement deep learning models for 3D computer vision tasks, including object detection, segmentation, and depth estimation. • Develop and maintain end-to-end machine learning pipelines encompassing data preprocessing, model training, evaluation, and deployment. • Optimize models for real-time inference and deploy them using cloud platforms such as AWS SageMaker or GCP Vertex AI. • Monitor deployed models, analyze performance metrics, and implement retraining strategies to ensure sustained accuracy and reliability. • Document methodologies, experiments, and findings; actively participate in code reviews and technical discussions. • Stay abreast of the latest research and advancements in machine learning and computer vision to inform model development.

Job Requirements

  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; a master’s degree or relevant research experience is preferred.
  • Minimum of four years of experience in developing and deploying machine learning models, with at least two years focused on computer vision applications.
  • Proficiency in Python and experience with deep learning frameworks such as PyTorch or TensorFlow; familiarity with models like DINOv2, ViTs, or SAM.
  • Hands-on experience deploying ML models on cloud platforms (e.g., AWS, GCP) and building containerized services using Docker and Flask/FastAPI.
  • Familiarity with data annotation tools and labeling strategies for supervised learning; understanding of data management best practices.
  • Experience with geospatial data, including photogrammetry, LiDAR, or satellite imagery, is a plus.

Benefits

  • Professional development through courses, seminars, and certifications.
  • Annual tech allowance.
  • Health benefits.
  • Stock options.
  • Paid time off and vacations.
  • Fully remote work.

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