AI ML Enginner

We are seeking a highly motivated AI/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.

Open Locations: Ahmedabad, Pune and Vadodara

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)
Develop and enhance OCR systems, including model fine-tuning and post-processing pipelines (LayoutLMv3, PaddleOCR, DocTR, Surya)
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
OCR systems
Experience with OCR technologies and model optimization
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)