Role Overview
You are a highly skilled Python Engineer with 58 years of experience in building AI driven systems, machine learning pipelines, and cloud based solutions. Your role involves close collaboration with Data Scientists and AI Engineers to develop scalable backend services, tools for AI agents, and intuitive interfaces that support the deployment, monitoring, and usability of advanced ML/LLM applications. You have strong expertise in Python, Machine Learning, Computer Vision, LLMs, and MLOps, with hands-on experience in deploying models and solutions on Microsoft Azure.
Key Responsibilities
- Build and maintain end-to-end machine learning solutions, including data preprocessing, model training, evaluation, and deployment.
- Develop and implement Machine Learning Algorithms, Computer Vision pipelines, and LLM based models.
- Apply statistical analysis, experimentation methods, and data modeling techniques to solve complex business problems.
- Implement automated ML workflows, versioning, and monitoring aligned with MLOps best practices.
- Design and develop scalable backend services and tools that support AI agents and ML-driven automation.
- Integrate ML models into production environments with robust APIs and microservices.
- Collaborate with cross-functional teams to create user-friendly interfaces and tools that improve usability of AI-driven applications.
- Perform exploratory data analysis (EDA), build dashboards, and present insights using data visualization tools.
- Work with large, complex datasets using SQL and Python-based data libraries.
- Deploy ML models and services on Azure Cloud, leveraging services such as Azure ML, AKS, Azure Functions, or App Services.
- Set up CI/CD pipelines for ML workloads, including automated training, testing, and deployment.
- Ensure reliability, scalability, and security of AI applications in production.
Qualification Required:
- Mandatory skills: Python, Machine Learning Algorithms, Model Training/Deployment, Computer Vision, LLM, Statistical Analysis, Data Visualization, SQL, Cloud Platform (Azure), MLOps.
- Desired soft skills: Strong communication and collaboration abilities, problem-solving mindset with ownership and accountability, ability to work in agile, fast-paced engineering environments.
Additional Details of the Company:
The engineer role will involve collaborating with Data Scientists and AI Engineers to develop and integrate scalable backend services, tools for agents, and intuitive user interfaces that support the deployment and usability of AI-driven applications. The Data Scientist role is to extract actionable insights from complex data using statistical analysis, machine learning, and data modeling to support strategic decision-making.
Industry: Banking
Role Overview
You are a highly skilled Python Engineer with 58 years of experience in building AI driven systems, machine learning pipelines, and cloud based solutions. Your role involves close collaboration with Data Scientists and AI Engineers to develop scalable backend services, tools for AI agents, and intuitive interfaces that support the deployment, monitoring, and usability of advanced ML/LLM applications. You have strong expertise in Python, Machine Learning, Computer Vision, LLMs, and MLOps, with hands-on experience in deploying models and solutions on Microsoft Azure.
Key Responsibilities
- Build and maintain end-to-end machine learning solutions, including data preprocessing, model training, evaluation, and deployment.
- Develop and implement Machine Learning Algorithms, Computer Vision pipelines, and LLM based models.
- Apply statistical analysis, experimentation methods, and data modeling techniques to solve complex business problems.
- Implement automated ML workflows, versioning, and monitoring aligned with MLOps best practices.
- Design and develop scalable backend services and tools that support AI agents and ML-driven automation.
- Integrate ML models into production environments with robust APIs and microservices.
- Collaborate with cross-functional teams to create user-friendly interfaces and tools that improve usability of AI-driven applications.
- Perform exploratory data analysis (EDA), build dashboards, and present insights using data visualization tools.
- Work with large, complex datasets using SQL and Python-based data libraries.
- Deploy ML models and services on Azure Cloud, leveraging services such as Azure ML, AKS, Azure Functions, or App Services.
- Set up CI/CD pipelines for ML workloads, including automated training, testing, and deployment.
- Ensure reliability, scalability, and security of AI applications in production.
Qualification Required:
- Mandatory skills: Python, Machine Learning Algorithms, Model Training/Deployment, Computer Vision, LLM, Statistical Analysis, Data Visualization, SQL, Cloud Platform (Azure), MLOps.
- Desired soft skills: Strong communication and collaboration abilities, problem-solving mindset with ownership and
