Senior AI/ML Engineer - Python/NLP

Description :

Role Overview :

We are looking for an experienced Senior AI/ML Engineer with strong expertise in Python to design, develop, and deploy machine learning models and AI solutions.

The ideal candidate will lead end-to-end ML projects, from data collection and preprocessing to model training, evaluation, deployment, and monitoring, while collaborating closely with data scientists, engineers, and product teams.

Key Responsibilities :

- Design, develop, and implement machine learning and AI models using Python and related libraries.

- Research and apply state-of-the-art ML algorithms, deep learning architectures, and NLP models.

- Conduct data preprocessing, feature engineering, and data augmentation to improve model performance.

- Experiment with supervised, unsupervised, and reinforcement learning techniques.

- Collaborate with engineering teams to deploy ML models to production (cloud or on-premise).

- Build and maintain APIs or microservices for serving ML models.

- Monitor deployed models for performance, drift, and retraining needs.

- Optimize models for latency, scalability, and resource efficiency.

- Work with structured and unstructured data sources, including text, images, video, and sensor data.

- Perform exploratory data analysis (EDA), statistical analysis, and visualization.

- Ensure data quality, consistency, and availability for ML pipelines.

- Lead technical discussions and provide guidance on ML architecture and best practices.

- Mentor junior engineers and data scientists.

- Collaborate with product managers and stakeholders to translate business problems into ML solutions.

- Document ML models, pipelines, and processes for reproducibility and knowledge sharing.

Required Skills & Qualifications :

- Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or related field (PhD is a plus).

- 5 to 10 years of experience in AI/ML engineering or data science.

- Strong proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, Keras, or XGBoost.

- Experience with deep learning, NLP, computer vision, or reinforcement learning.

- Strong knowledge of statistics, probability, and linear algebra.

- Experience in data preprocessing, feature engineering, and model evaluation.

- Familiarity with cloud ML platforms such as AWS SageMaker, Azure ML, or GCP AI Platform.

- Experience with version control (Git), containerization (Docker), and CI/CD for ML pipelines.

- Strong problem-solving, analytical, and communication skills