AI & Machine LearningFull-timeOn-site

Deep Learning Engineer

Design and train deep neural networks at APPIT Software in Hyderabad, building high-performance models for language understanding, vision, and multimodal AI applications across enterprise products.

Hyderabad, India

Full-time

AI & Machine Learning

Responsibilities

Design, train, and optimize deep neural network architectures for production use cases
Implement custom model architectures using PyTorch for NLP, vision, and multimodal tasks
Conduct large-scale training experiments with distributed data-parallel and model-parallel strategies
Optimize training efficiency through mixed precision, gradient checkpointing, and curriculum learning
Build data loading and augmentation pipelines for efficient training on large datasets
Profile and debug model performance using PyTorch profiler and CUDA debugging tools

Requirements

3-5 years of experience in deep learning engineering
Expert-level PyTorch skills with experience writing custom layers, loss functions, and training loops
Strong understanding of neural network architectures (transformers, CNNs, RNNs, diffusion models)
Experience with distributed training (DDP, FSDP, DeepSpeed)
Solid mathematical foundations in linear algebra, calculus, and probability theory
Knowledge of GPU programming concepts and memory optimization techniques

Nice to Have

Experience with CUDA programming or custom CUDA kernels
Knowledge of neural architecture search or AutoML
Publications in deep learning research venues

Skills

PyTorchDeep LearningCUDADistributed TrainingTransformersMixed PrecisionPythonNeural Architecture Design

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Related Positions

AI & Machine LearningHybrid

Deep Learning Engineer

Design and train deep neural networks at APPIT Software in Hyderabad, building high-performance models for language understanding, vision, and multimodal AI applications across enterprise products.

Hyderabad, India

Full-time

AI & Machine Learning

Responsibilities

Design, train, and optimize deep neural network architectures for production use cases
Implement custom model architectures using PyTorch for NLP, vision, and multimodal tasks
Conduct large-scale training experiments with distributed data-parallel and model-parallel strategies
Optimize training efficiency through mixed precision, gradient checkpointing, and curriculum learning
Build data loading and augmentation pipelines for efficient training on large datasets
Profile and debug model performance using PyTorch profiler and CUDA debugging tools

Requirements

3-5 years of experience in deep learning engineering
Expert-level PyTorch skills with experience writing custom layers, loss functions, and training loops
Strong understanding of neural network architectures (transformers, CNNs, RNNs, diffusion models)
Experience with distributed training (DDP, FSDP, DeepSpeed)
Solid mathematical foundations in linear algebra, calculus, and probability theory
Knowledge of GPU programming concepts and memory optimization techniques

Nice to Have

Experience with CUDA programming or custom CUDA kernels
Knowledge of neural architecture search or AutoML
Publications in deep learning research venues

Skills

PyTorchDeep LearningCUDADistributed TrainingTransformersMixed PrecisionPythonNeural Architecture Design

Deep Learning Engineer

Responsibilities

Requirements

Nice to Have

Skills

Apply for this position

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Responsibilities

Requirements

Nice to Have

Skills

Apply for this position

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