Corover
Ai Ml Engineer
Develops, trains, and fine-tunes AI/ML models for use cases like text summarization, image matching, and speech recognition; builds feature-engineering pipelines, runs experiments, and deploys models to production (including government apps) using Python, PyTorch/TensorFlow, Hugging Face, Docker, and SageMaker.
- Compensation
- ₹2M–₹2.5M / yr
- Location
- Delhi / NCR
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Full time
- Experience
- 4+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- B.Tech / M.Tech in Computer Science, AI, Data Science, or equivalent
- 4-7 years of hands-on experience developing and fine-tuning AI/ML models
- Practical exposure to NLP, computer vision, or predictive analytics projects
- Experience implementing AI solutions using open-source or cloud frameworks
- Programming in Python, C++, and R
- Frameworks: PyTorch, TensorFlow, Keras, Hugging Face
- Libraries: pandas, NumPy, OpenCV, spaCy, Transformers
- Data handling with SQL, NoSQL, and data augmentation techniques
- Tools: Docker, SageMaker, MLflow, Git
- Evaluation metrics: F1, BLEU, ROUGE, AUC, precision-recall curves
Nice to have
- Professional certification in machine learning or deep learning
- Research papers, case studies, or significant open-source contributions
Full description
Educational Qualification:
- B.Tech / M.Tech in Computer Science, AI, Data Science, or equivalent.
- Professional certification in machine learning or deep learning preferred.
- Research papers, case studies, or significant open-source contributions(are preferred)
Experience:
- 47 years of hands-on experience in developing and fine-tuning AIIML models.
- Practical exposure to NLP, computer vision, or predictive analytics projects.
- Demonstrated experience in implementing Al solutions using open-source or cloud frameworks.
Key Responsibilities:
- Develop, train, and optimize AI/ML models for various use cases such as text summarizrtion, image matching, and speech recognition.
- Implement feature engineering pipelines and data pre-processing modules.
- Conduct experiments and document results to improve model accuracy and latency.
- Collaborate with Data Scientists and Engineers to deploy AI models in production.
- Perform error analysis and debugging to improve model stability.
- Ensure model outputs comply with Responsible Al guardrails and data protection norms.
- Support integration of AI components into existing government applications.
Technical Competencies:
- Programming Languages: Python, CH, R.
- Frameworks: PyTorch, TensorFlow, Keras, Hugging Face.
- Libraries: pandas, NumPy, OpenCV, spaCy, Transformers.
- Data Handling: SQL, NoSQL, data augmentation techniques.
- Cloud & Tools: Docker, SageMaker, MLflow, Git.
- Evaluation Metrics: Fl, BLEU, ROUGE, AUC, precision-recall curves