Description

You will design and deliver end-to-end machine learning solutions across various domains using Agile methodologies.

Responsibilities

• Build and deploy end-to-end machine learning pipelines using MLOps frameworks like Kubeflow Pipelines or Vertex AI.
• Develop computer vision applications involving image preprocessing, object detection, and image similarity.
• Implement NLP solutions including document classification, semantic similarity, NER, and sentiment analysis.
• Execute time series analysis using ARIMA, SARIMA, and LSTMs.
• Monitor model performance and manage CI/CD workflows for machine learning models.

Required Skills

• 3 to 7 years of experience in machine learning and statistical modelling.
• Proficiency in Python or R programming.
• Hands-on experience with Scikit-Learn, Pandas, TensorFlow, PyTorch, Keras, OpenCV, and XGBoost.
• Expertise in Computer Vision techniques such as SIFT, SURF, ORB, YOLO, SSD, and Siamese networks.
• Deep understanding of NLP including Vector Space modeling, LSTMs, Attention modeling, BERT, and Transformers.
• Experience with feature engineering, dimensionality reduction (PCA), and hyperparameter tuning.
• Knowledge of ensemble techniques including Bagging, Boosting, and Stacking.
• Familiarity with cloud platforms, specifically GCP (Vertex AI, Document AI, Contact Center AI), or Azure/AWS.

Preferred Skills

• Experience with GCP-specific services like Speech-to-Text, Dialogflow, and Video Intelligence.

Key Skills

Education

ANY GRADUATE