Job Summary
Job Description: AI/ML Engineer
Role: AI/ML Engineer
Employment Type: Full Time
Job Summary
We are seeking a skilled and passionate AI/ML Engineer with strong experience in Machine Learning, Deep Learning, and MLOps using Python. The ideal candidate should have hands-on experience in designing, developing, deploying, and maintaining machine learning solutions, building end-to-end ML pipelines, and ensuring scalable AI model delivery across enterprise applications. Exposure to Generative AI and cloud platforms will be an added advantage.
Key Responsibilities
Design, develop, and maintain scalable Machine Learning and Deep Learning solutions using Python.
Build, train, evaluate, and deploy machine learning models for predictive analytics, forecasting, recommendation systems, NLP, or computer vision use cases.
Collaborate closely with Data Engineers, Business Analysts, Product Owners, and stakeholders to understand requirements and define AI/ML solutions.
Participate in Agile ceremonies including Sprint Planning, Daily Stand-ups, Retrospectives, and Grooming sessions.
Analyze model performance, identify improvement opportunities, and work with teams to enhance solution effectiveness.
Prepare and maintain model documentation, experiment tracking, feature engineering workflows, and deployment reports.
Integrate machine learning models with CI/CD and MLOps pipelines to enable continuous deployment and monitoring.
Ensure model accuracy, scalability, reliability, and governance across critical business applications.
Perform data analysis, feature engineering, model validation, and performance optimization where required.
Contribute to AI/ML best practices, model lifecycle management, and framework enhancements.
Mandatory Skills
Machine Learning
Strong hands-on experience in Machine Learning model development and deployment.
Experience with supervised and unsupervised learning algorithms.
Experience in feature engineering, model evaluation, and model performance optimization.
Understanding of Machine Learning algorithms, statistical methods, and predictive analytics.
Deep Learning
Experience with Deep Learning frameworks such as TensorFlow, PyTorch, or Keras.
Experience developing NLP, Computer Vision, or Generative AI solutions.
MLOps
Experience with MLflow or similar MLOps platforms.
Knowledge of model versioning, experiment tracking, deployment, and monitoring.
Programming
Strong proficiency in Python programming.
Experience with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or similar frameworks.
Good to Have
Experience with Generative AI, LLMs, RAG, or Agentic AI frameworks.
Experience with cloud platforms (GCP/Azure/AWS).
Knowledge of Big Data technologies such as Spark or Databricks.
Experience with Vector Databases and semantic search solutions.
Containerization knowledge (Docker).
Experience with CI/CD tools such as Jenkins, Azure DevOps, or GitHub Actions.
Experience working in enterprise-scale AI/ML applications.
Key Responsibilities
Job Description: AI/ML Engineer
Role: AI/ML Engineer
Employment Type: Full Time
Job Summary
We are seeking a skilled and passionate AI/ML Engineer with strong experience in Machine Learning, Deep Learning, and MLOps using Python. The ideal candidate should have hands-on experience in designing, developing, deploying, and maintaining machine learning solutions, building end-to-end ML pipelines, and ensuring scalable AI model delivery across enterprise applications. Exposure to Generative AI and cloud platforms will be an added advantage.
Key Responsibilities
Design, develop, and maintain scalable Machine Learning and Deep Learning solutions using Python.
Build, train, evaluate, and deploy machine learning models for predictive analytics, forecasting, recommendation systems, NLP, or computer vision use cases.
Collaborate closely with Data Engineers, Business Analysts, Product Owners, and stakeholders to understand requirements and define AI/ML solutions.
Participate in Agile ceremonies including Sprint Planning, Daily Stand-ups, Retrospectives, and Grooming sessions.
Analyze model performance, identify improvement opportunities, and work with teams to enhance solution effectiveness.
Prepare and maintain model documentation, experiment tracking, feature engineering workflows, and deployment reports.
Integrate machine learning models with CI/CD and MLOps pipelines to enable continuous deployment and monitoring.
Ensure model accuracy, scalability, reliability, and governance across critical business applications.
Perform data analysis, feature engineering, model validation, and performance optimization where required.
Contribute to AI/ML best practices, model lifecycle management, and framework enhancements.
Mandatory Skills
Machine Learning
Strong hands-on experience in Machine Learning model development and deployment.
Experience with supervised and unsupervised learning algorithms.
Experience in feature engineering, model evaluation, and model performance optimization.
Understanding of Machine Learning algorithms, statistical methods, and predictive analytics.
Deep Learning
Experience with Deep Learning frameworks such as TensorFlow, PyTorch, or Keras.
Experience developing NLP, Computer Vision, or Generative AI solutions.
MLOps
Experience with MLflow or similar MLOps platforms.
Knowledge of model versioning, experiment tracking, deployment, and monitoring.
Programming
Strong proficiency in Python programming.
Experience with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or similar frameworks.
Good to Have
Experience with Generative AI, LLMs, RAG, or Agentic AI frameworks.
Experience with cloud platforms (GCP/Azure/AWS).
Knowledge of Big Data technologies such as Spark or Databricks.
Experience with Vector Databases and semantic search solutions.
Containerization knowledge (Docker).
Experience with CI/CD tools such as Jenkins, Azure DevOps, or GitHub Actions.
Experience working in enterprise-scale AI/ML applications.