We are seeking a highly motivated ML Engineer & Developer with 4 - 5 years of experience in core machine learning and deep learning.

The ideal candidate will have strong expertise in statistical analysis, NLP, and Computer Vision, along with hands-on experience in transformer-based models and OCR systems.

This role also involves contributing to R&D initiatives and mentoring junior team members while staying up to date with the latest advancements in AI.

Location : Noida, Ahmedabad, Mumbai, Pune.

Key Responsibilities :

- Design, develop, and deploy machine learning and deep learning models for real-world applications.

- Perform statistical analysis and data exploration to derive meaningful insights (Time series analysis & Forecasting, predictive analysis).

- Build and optimize NLP and Computer Vision pipelines for various use cases.

- Fine-tune transformer-based models for tasks such as text classification, entity recognition, and vision tasks (BERT, LayoutLMv3, Vision Transformers, etc).

- Build document AI systems (text + layout + image).

- Perform feature engineering and EDA.

- Work on domain-specific keyword extraction systems.

- Contribute to R&D in NLP, OCR, and multimodal AI.

- Optimize models for accuracy, scalability, and performance.

- Collaborate with cross-functional teams to integrate ML models into production systems.

- Continuously evaluate and adopt new AI/ML techniques, tools, and frameworks.

- Mentor and guide junior engineers, helping them understand core concepts and best practices.

- Maintain documentation and ensure knowledge sharing within the team.

Required Skills & Experience :

- 4 - 5 years of hands-on experience in AI/ML development.

- Strong foundation in ML, Deep Learning, Statistics & Mathematics.

- Expertise in NLP + Computer Vision.

- Hands-on with: Transformer models (e.g., BERT, Vision Transformers) and fine-tuning techniques.

- Proficiency in Python and ML/DL frameworks such as TensorFlow /PyTorch.

- Experience in building end-to-end ML pipelines and strong algorithmic thinking.

- Understanding of data preprocessing, feature engineering, and model evaluation techniques.

- Strong problem-solving skills and ability to work on R&D-focused tasks.

Nice to Have :

- Experience with Generative AI and deep learning architectures (LLMs, diffusion models, etc).

- Model optimization (quantization, pruning).

- Familiarity with MLOps practices and model deployment workflows.

- Experience with cloud platforms (Azure, AWS, or GCP).

- Knowledge of vector databases and embedding techniques.

- Experience with annotation tools and dataset creation for OCR/NLP tasks.

- Exposure to model optimization techniques (quantization, pruning, distillation).