Lead Assistant Manager

2 weeks ago


Gurugram India EXL IT service management Full time

Job Description Job Summary: We are looking for a motivated and skilled Machine Learning Engineer to join our team. The ideal candidate will have hands-on experience in building, deploying, and maintaining machine learning models and pipelines. You will collaborate closely with data scientists, software engineers, and product teams to turn data insights into scalable, production-ready solutions. Key Responsibilities: - Design, develop, and deploy machine learning models and algorithms for real-world applications. - Collaborate with data scientists to understand model requirements and translate prototypes into production code. - Preprocess, clean, and analyze large datasets to improve model performance and accuracy. - Optimize and fine-tune models using hyperparameter tuning, feature engineering, and cross-validation. - Build and maintain scalable data pipelines and automated workflows for model training and deployment. - Monitor and troubleshoot deployed models, ensuring reliability and performance in production environments. - Work with engineering teams to integrate ML solutions into existing products and services. - Stay updated with the latest advancements in machine learning and apply best practices. Qualifications: - Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field. - 2-5 years of experience in machine learning or data science roles. - Strong programming skills in Python and experience with ML libraries such as TensorFlow, PyTorch, scikit-learn, or similar. - Solid understanding of machine learning concepts, algorithms, and statistical methods. - Experience with data processing tools and frameworks (e.g., Pandas, NumPy, Spark). - Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) is a plus. - Knowledge of software engineering best practices, version control (Git), and CI/CD pipelines. - Strong problem-solving skills and the ability to work both independently and collaboratively.



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