Senior Machine Learning Engineer - Hybrid (Chennai/Coimbatore) (India)

Responsibilities

• Design and develop machine learning models and algorithms specifically focused on English language processing and natural language understanding.
• Apply advanced techniques in deep learning, natural language processing, and machine translation to extract meaningful insights and patterns from large English language datasets.
• Collaborate with cross-functional teams to identify business requirements and translate them into technical solutions using machine learning approaches.
• Conduct thorough research and stay up-to-date with the latest advancements in machine learning techniques and algorithms related to English language processing.
• Perform data preprocessing, feature engineering, and model training to optimize the performance of machine learning models.
• Evaluate and fine-tune the performance of existing machine learning models to improve accuracy, efficiency, and scalability.
• Collaborate with software engineers to integrate machine learning models into production systems and ensure their robustness and scalability.
• Mentor and provide guidance to junior members of the team, sharing your knowledge and expertise in machine learning techniques and best practices.
• Stay current with emerging trends in machine learning and contribute to the development of creative solutions to address business challenges.
• Document research findings, methodologies, and implementation details in technical reports and present them to both technical and non-technical stakeholders.

Qualifications

• Master’s degree in CS/Statistics/Data Science, with a specialization in machine learning or equivalent experience
• Strong background in machine learning, deep learning, and natural language processing.
• Extensive experience in developing and implementing machine learning models and algorithms using frameworks such as TensorFlow, PyTorch, or Keras.
• Proficiency in programming languages such as Python and experience with relevant libraries and tools for data manipulation and analysis (e.g., NumPy, pandas).
• Solid understanding of English language processing techniques, including but not limited to sentiment analysis, entity recognition, and part-of-speech tagging.
• Proven track record of successfully delivering machine learning projects and solutions in a professional setting.
• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and experience deploying machine learning models in production environments.
• Excellent problem-solving and analytical skills, with the ability to work on complex data-driven problems and propose innovative solutions.