AI Engineer (HS_Kitchen)

LG Soft India; Bengaluru; On-site; INR 1,400,000 - 2,400,000; Full time

Job summary

LG Soft India in Bangalore is seeking an AI/ML Engineer specializing in Edge AI computing to design, develop, and deploy models on resource-constrained devices. The role emphasizes ML/DL fundamentals, model optimization, and hands-on experience with standard AI frameworks.

Responsibilities include building end-to-end ML pipelines, tuning models, applying transfer learning, and benchmarking for latency and efficiency. Collaboration with embedded systems teams is essential.

Qualifications

• 2-5 years of AI/ML experience
• Experience with edge devices and deployment
• Strong fundamentals in ML/DL and math

Responsibilities

• Design, develop, train, and optimize ML/DL models for edge computing environments.
• Implement and deploy AI solutions on low-resource platforms with focus on performance and power efficiency.
• Develop end-to-end ML pipelines: data preprocessing, feature engineering, model training, validation, deployment.
• Perform model tuning, quantization, pruning for production deployment.
• Apply transfer learning to improve model accuracy and reduce training effort.
• Evaluate/benchmark models for latency and memory usage.
• Collaborate with cross-functional teams to integrate AI into embedded/edge systems.
• Analyze model performance and improve accuracy, robustness, scalability.
• Stay updated with AI, DL, and Edge Computing advancements.

Job description

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

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.