Job Description – AI/ML Engineer (Edge AI & Deep Learning)

Organization - LG Soft India, Bangalore

Position: AI/ML Engineer – Edge AI Computing
Experience: 2-5 Years (can be adjusted based on requirement)
Location: Bangalore / Noida
Department: AI Research & Development

Job Summary

We are seeking a highly skilled AI/ML Engineer with strong expertise in Machine Learning, Deep Learning, and Edge AI Computing. The candidate will be responsible for designing, developing, optimizing, and deploying AI models on resource-constrained edge devices. The role requires deep understanding of ML/DL fundamentals, model optimization techniques, mathematical foundations of neural networks, and hands-on experience with industry-standard AI frameworks and algorithms.

Key Responsibilities

• Design, develop, train, and optimize Machine Learning and Deep Learning models for edge computing environments.
• Implement and deploy AI solutions on low-resource computing platforms with focus on performance, accuracy, and power efficiency.
• Develop and maintain end-to-end ML pipelines including data preprocessing, feature engineering, model training, validation, and deployment.
• Perform model tuning, optimization, quantization, pruning, and verification for production deployment.
• Apply transfer learning techniques to improve model accuracy and reduce training efforts.
• Evaluate and benchmark AI models for latency, memory consumption, and computational efficiency.
• Collaborate with cross-functional teams to integrate AI algorithms into embedded and edge systems.
• Analyze model performance and continuously improve accuracy, robustness, and scalability.
• Stay updated with the latest advancements in AI, Deep Learning, and Edge Computing technologies.

Required Technical Skills

AI/ML Fundamentals

• Strong understanding and hands-on experience in:
  • Machine Learning (ML)
  • Deep Learning (DL)
  • Model Optimization & Verification
  • Transfer Learning
  • Statistical Modeling
  • Predictive Analytics

Machine Learning & Deep Learning Frameworks

• TensorFlow
• PyTorch
• Keras
• Scikit-Learn

Model Development Experience

Hands-on experience with:

• CNN (Convolutional Neural Networks)
• LSTM (Long Short-Term Memory)
• GRU (Gated Recurrent Unit)
• Regression Models
• Random Forest
• XGBoost
• LightGBM
• ARIMA/SARIMA Time Series Models

Programming Skills

• Strong Python Programming
• Good C++ Programming Skills
• Experience in algorithm design and optimization