Job Description

• Collaborate with cross-functional teams, including automation developers and business analysts, to understand the requirements of Intelligent Automation projects and identify areas where Machine Learning can be leveraged.
• Design and develop machine learning models and algorithms tailored to the specific needs, ensuring scalability, accuracy, and reliability.
• Implement and maintain ML pipelines for data preprocessing, feature engineering, model training, evaluation, and deployment.
• Perform data analysis and identify relevant data sources to extract valuable insights for enhancing automation workflows.
• Conduct thorough testing and validation of ML models to ensure their robustness and accuracy in real-world scenarios.
• Monitor and optimize ML models' performance, making necessary adjustments and improvements as needed.
• Document all ML-related processes, code, and project details comprehensively for future reference and knowledge sharing.
• Be the go-to expert for all Python-related automation development, including automation infrastructure, ensuring its smooth functioning, performance optimization, and security.

Qualifications

B.E/B.Tech

Additional Information

•    Bachelor's or Master's degree in Engineering (Preferred: Computer Science, Data Science, Machine Learning, or a related field.)

•    Proven work experience as a Machine Learning Specialist or a similar role, with 6-8 years of relevant industry experience.

•    Strong proficiency in Python programming and its associated libraries for Machine Learning, such as NumPy, Pandas, SciPy, Scikit-learn, TensorFlow, or PyTorch.

•    Hands-on experience in designing and implementing machine learning models for various applications, with a focus on natural language processing (NLP), computer vision, or predictive analytics.

•    Solid understanding of ML algorithms, statistical concepts, and data evaluation techniques.

•    Familiarity with RPA technologies and the ability to integrate ML solutions seamlessly into existing RPA workflows.

•    Strong problem-solving skills, attention to detail, and the ability to work independently or as part of a team.

•    Excellent communication skills, both verbal and written, to effectively convey technical concepts to non-technical stakeholders.