Associate ML Scientist (Computer Vision) arun.raja@dhira.ai

Associate ML Scientist (Computer Vision) resume to arun.raja@dhira.ai

Job Title: Associate Machine Learning Scientist (Computer Vision Specialization)

Location:

Position Summary

Associate Machine Learning (ML) Scientist

Key Responsibilities

• Develop robust, scalable machine learning models addressing complex computer vision challenges.
  
• Assist in the design and implementation of image and video analysis models, including object detection, face recognition, and image classification.
  
• Translate real-world challenges into well-defined AI/ML problem statements.
  
• Build and evaluate AI solutions through rigorous experimentation and performance benchmarking.
  
• Optimize and deploy computer vision models on various platforms, including edge and mobile devices.
  
• Curate, preprocess, and manage image and video datasets for model development and validation.
  
• Define and apply appropriate evaluation metrics for computer vision tasks, including accuracy, precision, recall, F1-score, and real-time inference benchmarks.
  
• Collaborate with cross-functional teams, including software engineers, product managers, and domain specialists, to deliver end-to-end AI solutions.
  
• Stay current with emerging research and best practices in computer vision, deep learning, and related fields.
  

Requirements

• Educational Background:

  Bachelors, Master’s, or equivalent degree in Computer Science, Electrical Engineering, Applied Mathematics, Statistics, Physics, or a related quantitative discipline.

• Experience:

  3–6 years of professional experience in developing and deploying machine learning solutions, with a strong focus on computer vision applications.

• Technical Skills:

Proficiency in Python and ML libraries such as TensorFlow, PyTorch, OpenCV, and scikit-learn.

Solid understanding of deep learning architectures for image and video processing (e.g., CNNs, ResNet, MobileNet, EfficientNet).

Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker) is preferred.

• Strong communication skills

  with the ability to translate technical concepts into actionable insights for cross-functional teams.

• Passion for applied machine learning

  and a willingness to adapt to diverse problem domains and real-world constraints.

Preferred Qualifications

• Prior experience deploying computer vision models on mobile or edge devices.
  
• Experience working with face detection and recognition models.
  
• Familiarity with MLOps practices for model deployment, monitoring, and lifecycle management.
  
• Demonstrated ability to work independently and collaboratively in fast-paced, solution-driven environments.
  
• Exposure to ethical and responsible AI practices in computer vision applications.