Deep Learning Engineer

Job Summary

We are seeking a highly skilled Deep Learning Engineer to develop, train, optimize, and deploy state-of-the-art deep learning models for real-world AI applications. The ideal candidate will have expertise in neural networks, computer vision, natural language processing (NLP), generative AI, and large-scale machine learning systems.

You will work with AI researchers, data scientists, software engineers, and product teams to build next-generation AI solutions that power intelligent products and services across industries.

Key Responsibilities

Deep Learning Model Development

• Design, develop, and optimize deep neural network architectures.
• Build and train machine learning and deep learning models using large-scale datasets.
• Develop solutions for Computer Vision, NLP, Speech AI, and Generative AI applications.
• Fine-tune foundation models and Large Language Models (LLMs).

Model Training & Optimization

• Perform hyperparameter tuning and model optimization.
• Improve model accuracy, scalability, and efficiency.
• Implement distributed training strategies for large-scale models.
• Conduct model evaluation and validation.

Production Deployment

• Deploy deep learning models into production environments.
• Develop scalable inference pipelines.
• Monitor model performance and retrain models as required.
• Implement MLOps best practices.

Research & Innovation

• Stay updated on the latest AI research and advancements.
• Experiment with emerging architectures and techniques.
• Collaborate with research teams to translate innovations into production solutions.
• Publish technical findings and contribute to AI knowledge sharing.

Collaboration

• Work closely with data engineering teams to build data pipelines.
• Partner with product teams to define AI requirements.
• Support AI integration across enterprise applications.
• Mentor junior engineers and contribute to technical leadership.

Required Qualifications

Education

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Mathematics, or a related field.

Experience

• 3+ years of experience in Deep Learning, Machine Learning, or AI Engineering.
• Experience developing and deploying production-grade AI solutions.
• Strong understanding of neural networks and advanced AI algorithms.

Technical Skills

Programming Languages

• Python
• C++
• SQL

Deep Learning Frameworks

• PyTorch
• TensorFlow
• Keras
• JAX

AI & Machine Learning

• Deep Neural Networks (DNN)
• CNNs (Convolutional Neural Networks)
• RNNs & LSTMs
• Transformers
• Generative AI
• Reinforcement Learning
• Transfer Learning

Specialized Areas

• Computer Vision
• Natural Language Processing (NLP)
• Large Language Models (LLMs)
• Multimodal AI
• Speech Recognition

Cloud & Infrastructure

• AWS
• Azure
• Google Cloud Platform (GCP)
• Docker
• Kubernetes

Data & MLOps

• Apache Spark
• MLflow
• Kubeflow
• Airflow
• Git/GitHub

Preferred Certifications

• NVIDIA Deep Learning Institute Certifications
• Google Cloud Professional Machine Learning Engineer
• Microsoft Azure AI Engineer Associate
• Amazon Web Services Machine Learning Specialty

Preferred Skills

• Model Optimization & Quantization
• Distributed Training
• CUDA Programming
• GPU Acceleration
• AI Model Deployment
• MLOps & Model Monitoring
• Research and Innovation
• Problem Solving & Communication Skills

Benefits

• Competitive Base Salary
• Annual Performance Bonus
• RSU/Stock Grants
• Medical, Dental & Vision Insurance
• Flexible Hybrid Work Model
• Learning & Development Programs
• Career Advancement Opportunities