Deep Learning Engineer

**Company:** Hiringhood

**Employment Type:** Full Time

**Experience:** 3–6 Years

**No. of Positions:** 1

**CTC:** ₹22–40 LPA

**Location:** Hyderabad, Telangana

**Qualification:** Bachelor's Degree

**Office Timings:** 09:00 – 18:00

**Notice Period:** Immediate Joiner

**Onsite Feasibility:** Yes

Job Description

We are seeking a skilled Deep Learning Engineer to design, train, and deploy advanced neural network architectures. This role goes beyond fine-tuning pretrained models, requiring hands-on experience building deep learning models from scratch. You will work on high-impact problems across areas such as computer vision, NLP, and multimodal AI, contributing directly to the development of innovative AI products.

Must Have Skills

* Design, implement, and train deep neural networks (e.g., CNNs, RNNs, Transformers, Diffusion Models).

* Python (P1), PyTorch (P2) or TensorFlow (P2).

* Neural network theory – backpropagation, activation functions, initialization, and optimization.

* Training on large datasets, including distributed training and GPU acceleration.

* Debugging training instabilities, overfitting, or mode collapse.

* 3+ years of experience in training deep learning models end-to-end, beyond pre-trained fine-tuning.

* Strong programming skills in Python, with hands-on experience in PyTorch or TensorFlow.

* Solid understanding of neural network theory: backpropagation, activation functions, initialization, and optimization.

* Experience training on large datasets, including distributed training and GPU acceleration.

* Ability to design data pipelines and manage the model lifecycle in production environments.

* Strong intuition for debugging training instabilities, overfitting, or mode collapse.

Good to Have Skills

* Productionizing models using tools like ONNX, TensorRT, or quantization.

* Knowledge of LLMs, diffusion models, or custom neural architectures.

* Contributions to open-source ML projects or published research papers.

* Experience working with multimodal inputs (e.g., vision + text, audio + text).

Key Responsibilities

* Design, implement, and train deep neural networks (e.g., CNNs, RNNs, Transformers, Diffusion Models) from scratch.

* Select and optimize loss functions, training algorithms, regularization techniques, and data augmentation strategies.

* Analyze model performance using metrics, visualizations, ablations, and interpretability tools.

* Write clean, modular, and efficient code for research experiments and production deployment.

* Collaborate with ML researchers, data engineers, and product teams to bring models into production.

* Stay updated with the latest AI/ML research and assess innovations for adoption.

* Conduct internal benchmarks and document model development processes.

Required Qualifications

* 3+ years of experience in training deep learning models end-to-end, beyond pre-trained fine-tuning.

* Strong programming skills in Python, with hands-on experience in PyTorch or TensorFlow.

* Solid understanding of neural network theory: backpropagation, activation functions, initialization, and optimization.

* Experience training on large datasets, including distributed training and GPU acceleration.

* Ability to design data pipelines and manage the model lifecycle in production environments.

* Strong intuition for debugging training instabilities, overfitting, or mode collapse.

Preferred Qualifications

* Experience in productionizing models using tools like ONNX, TensorRT, or quantization.

* Knowledge of LLMs, diffusion models, or custom neural architectures.

* Contributions to open-source ML projects or published research papers.

* Experience working with multimodal inputs (e.g., vision + text, audio + text).

Soft Skills

* Strong analytical and problem-solving abilities.

* Ability to work independently and collaboratively in research-driven environments.

* Passion for keeping up with the latest AI/ML trends and breakthroughs.

* Clear communication skills for sharing technical insights with cross-functional teams.

Pay: ₹2,200,000.00 - ₹4,000,000.00 per year

Work Location: In person