About the Role : Key Responsibilities :

- Architect scalable Machine Learning pipelines and production-ready AI systems.
- Build, train, fine-tune, evaluate, and deploy advanced Machine Learning and Deep Learning models.
- Drive initiatives in Generative AI , Large Language Models (LLMs), NLP, Computer Vision, and predictive analytics.
- Design and implement end-to-end MLOps pipelines for model deployment, monitoring, versioning, and continuous improvement.
- Collaborate with product owners, business stakeholders, engineering teams, and data scientists to translate business requirements into AI-driven solutions.
- Mentor and provide technical guidance to junior AI/ML engineers and data scientists.
- Perform advanced data analysis, feature engineering, model optimization, and performance tuning.
- Ensure AI models are scalable, secure, reliable, and aligned with organizational standards.
- Stay updated with emerging AI technologies, research, and industry best practices, driving innovation across projects.

Required Skills & Technology Stack : Programming Languages :

- Python (mandatory)
- R
- Java

AI/ML Frameworks & Libraries :

- TensorFlow
- PyTorch
- Keras
- Scikit-learn
- OpenCV
- Hugging Face Transformers
- LangChain / LlamaIndex (preferred)

Data & Analytics :

- Pandas
- NumPy
- SQL
- Apache Spark
- Data Engineering concepts

Cloud Platforms :

- AWS AI/ML Services
- Microsoft Azure AI Services
- Google Cloud Platform (Vertex AI)

DevOps & MLOps :

- Git




- Docker
- Kubernetes
- MLflow
- CI/CD Pipelines
- Model Monitoring & Deployment

AI Expertise :

- Machine Learning
- Deep Learning
- Generative AI
- Large Language Models (LLMs)
- Natural Language Processing (NLP)
- Computer Vision
- Recommendation Systems
- Model Deployment & Optimization
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- AI Governance and Responsible AI

Required Experience :

- 6-9+ years of experience in Artificial Intelligence, Machine Learning, or Data Science.
- Proven experience delivering end-to-end AI/ML solutions in production environments.
- Strong experience in designing scalable AI architectures and deploying enterprise-grade ML models.
- Experience working with cloud-native AI services and MLOps practices.
- Experience mentoring junior engineers and leading technical initiatives.
- Exposure to Agile development methodologies and cross-functional collaboration.
- Excellent analytical, problem-solving, and communication skills.

Preferred Certifications :

- Microsoft Certified: Azure AI Engineer Associate
- AWS Certified Machine Learning - Specialty
- Google Skilled Machine Learning Engineer
- TensorFlow Developer Certificate
- Databricks Machine Learning Professional (preferred)

Educational Qualifications :

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.

📌 Senior Ai Engineer / Senior Machine Learning Specialist (Gurugram)
🏢 IMPRONICS DIGITECH PRIVATE
📍 Gurugram