Senior Technical Lead - AI and Machine Learning

About the Role

This position involves architecting, optimizing, and assessing machine learning algorithms, mainly focusing on time series forecasting and natural language processing. The role demands technical excellence to deliver scalable solutions while upholding development standards and actively contributing to project goals through advanced usage of Python, Spark, Kafka, and relevant ML toolkits.

Core Responsibilities

• Design and implement time series forecasting models leveraging Python, scikit-learn, TensorFlow, and StatsModels, ensuring high accuracy and reliability.
• Handle integration and transformation of large-scale streaming datasets with Apache Kafka and Spark for real-time feature engineering within ML pipelines.
• Conduct rigorous evaluation of machine learning models using methods such as cross-validation, ROC/AUC analysis, Precision/Recall, F1-score, and Confusion Matrices to guarantee top-tier performance.
• Employ NLP tools and techniques, including NLTK and SpaCy, for preprocessing and analyzing textual data tailored for forecasting use cases.
• Optimize workflows for model training and deployment using Apache Airflow and Hadoop to maintain efficiency and scalability in production settings.
• Collaborate closely with the development team to promote and apply Python coding standards and best practices in machine learning development.
• Develop comprehensive technical documentation and progress reports covering project status, encountered risks, and strategies for their mitigation.

Required Skills and Qualifications

• Expertise in machine learning and natural language processing encompassing supervised, unsupervised, deep learning, and reinforcement learning techniques.
• Strong command over Python and associated libraries such as Numpy, Pandas, scikit-learn, TensorFlow, PyTorch, XGBoost, and LightGBM for model development and assessment.
• Deep understanding of time series analysis and forecasting methods.
• Proficient in Apache Spark and Kafka for distributed data processing and real-time stream analytics.
• Thorough knowledge of machine learning model evaluation metrics and practices, including cross-validation and statistical analyses.
• Practical experience utilizing NLP frameworks like NLTK and SpaCy to process text data effectively.

Additional Information

The role is based in Bengaluru, India, at a leading global technology company focused on innovation and digital transformation. Candidates with any graduate degree are eligible to apply.