AI Engineer

Job Title

Location:

Salary:

Experience:

computer vision

machine learning

Key Responsibilities

• Develop and optimize image processing and deep learning algorithms for real-time inspection systems.
• Apply deep learning techniques including CNNs, GANs, Transformers, etc., to solve vision-related tasks.
• Work on full-cycle deployment of ML/DL solutions from model training to production.
• Handle large datasets and implement solutions for unsupervised learning and anomaly detection.
• Collaborate cross-functionally with product and engineering teams in a hybrid work environment.
  

Required Skills & Experience

• Minimum 4 years of experience in:
• Artificial Intelligence
• Machine Learning
• Deep Learning
• Minimum 2 years of experience in:
• Computer Vision or Image Processing
• Hands-on experience with Python or C++; experience with Linux is preferred.
• Proficiency in DL frameworks such as TensorFlow, PyTorch, etc.
• Experience with at least one of the following: GANs, Autoencoders, Semantic Segmentation.
• Strong mathematical background and ability to translate problems into mathematical models.
• Experience with large-scale datasets and real-world ML deployment is a plus.
  

Educational Qualifications

• B.Tech/M.Sc: Minimum 4+ years of relevant experience
• M.Tech/MS: Minimum 3+ years of relevant experience
• Ph.D.: Freshers eligible
• Degrees must be from Tier-1 institutes only (e.g., IIT, IIIT, IISC, NIT, VIT, PSG, CEG)
  

Candidate Requirements

• Total experience must not exceed 9 years
• No frequent job changes – must have minimum 2 years tenure in current/previous roles
• Open to relocate to Chennai (hybrid work model)
• Candidates must not be employed by restricted clients or vendors
• Preference for candidates from product-based companies
• Candidates with semiconductor industry experience are also welcome (regardless of institution)
  

Preferred Background

• B.Tech/M.Tech in CSE, IT, ECE, Data Science
• Background in Semiconductor, Computer Vision, or AI Research is advantageous
  

Interview Process

• 3 Technical Rounds
• 2 Non-Technical Rounds