About the Role :

We are seeking highly experienced Senior Machine Learning Engineers to join our AI team. Candidates should have 4+ years of experience building and deploying production-grade ML models. You will be responsible for end-to-end ML solutions, data-driven projects, and creating scalable, high-performance AI systems.

Key Responsibilities :

- Design, develop, and deploy machine learning and deep learning models.

- Conduct advanced data preprocessing, feature engineering, and model evaluation.

- Implement optimization techniques for algorithm performance and scalability.

- Work with Python frameworks such as Scikit-learn, TensorFlow, PyTorch, and Keras for model development.

- Build interactive dashboards using Streamlit, Plotly, and other visualization tools.

- Collaborate with cross-functional teams including data engineering, product, and software development.

- Research and implement state-of-the-art ML/AI algorithms.

- Deploy models using FastAPI, Flask, Docker, or Kubernetes.

- Monitor and maintain production models for performance and reliability.

Required Skills & Expertise :

- Programming Languages : Python (NumPy, Pandas, Matplotlib, Seaborn, etc.), SQL.

- Machine Learning : Supervised & unsupervised learning, regression, classification, clustering, recommendation systems, ensemble methods, Scikit-learn.

- Deep Learning : CNNs, RNNs, LSTMs, GRUs, Transformers, attention mechanisms, TensorFlow, PyTorch, Keras.

- Natural Language Processing (NLP) : Text preprocessing, embeddings, transformers (BERT, GPT), sentiment analysis, NER.

- Computer Vision : Image classification, object detection, segmentation.

- Time Series Analysis : Forecasting using ARIMA, Prophet, LSTM, RNN.

- Algorithms & Data Structures : Strong foundation in algorithm design, complexity analysis, probability, statistics, and optimization.

- MLOps / Deployment : FastAPI/Flask, Docker, Kubernetes, CI/CD pipelines, cloud deployment (AWS/GCP/Azure).

- Data Management : SQL, NoSQL, ETL pipelines, big data frameworks (Spark, Hadoop).

- Visualization & Reporting : Streamlit, Plotly, Matplotlib, Seaborn, interactive dashboards.