About the role

Position Title
Assistant Manager, Automation Team
Department
Cyber
Location
Noida
Reports To
Senior Manager
Job Summary:
The Machine Learning Engineer is responsible for designing, developing, deploying, business value through predictive analytics, intelligent automation, anomaly strong expertise in data science, machine learning algorithms, MLOps, cloud collaborate with business and technical teams to build scalable AI solutions Key Responsibilities:
Machine Learning Solution Development
Design, develop, and implement Machine Learning and Artificial Intelligence Build predictive, classification, clustering, anomaly detection, recommendation, Develop and optimize machine learning pipelines for large-scale datasets. Evaluate and compare different algorithms to select the most effective solution. Perform feature engineering, model training, validation, and performance Data Engineering & Analytics
Collect, process, clean, and transform structured and unstructured data from Perform exploratory data analysis (EDA) to identify trends, correlations, and Design scalable data pipelines to support model training and inference. Collaborate with data engineers and business stakeholders to ensure data Model Deployment & MLOps
Deploy machine learning models into production environments. Build and maintain automated ML pipelines for continuous integration, testing, Monitor model performance, drift, and accuracy over time. Implement MLOps best practices for version control, experimentation tracking, Develop APIs and services for model consumption by business applications.
AI & Advanced Analytics
Leverage Generative AI, Large Language Models (LLMs), and NLP technologies Build intelligent automation solutions by integrating AI models with business Research and evaluate emerging AI technologies and frameworks. Develop proof-of-concepts (POCs) and pilots to demonstrate business value.
Collaboration & Stakeholder Management
Work closely with business teams to understand requirements and translate Present technical findings and model outcomes to both technical and non-Collaborate with cross-functional teams including automation, cloud, security, Support AI solution adoption through documentation, training, and knowledge Total Experience:
7+
Releveant Experience:
4+
Qualifications:
Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Master's degree is preferred. Strong experience in Machine Learning model development and deployment. Hands-on experience with Python and ML frameworks such as Scikit-learn, Experience with Azure AI ecosystem, Azure ML, Azure OpenAI, and cloud-Understanding of MLOps practices, model lifecycle management, and production Strong problem-solving, analytical, and troubleshooting skills. Excellent communication and stakeholder management abilities. Ability to work independently and collaboratively in a fast-paced environment