IT Analyst Applications (MLOps Engineer) at Caterpillar in Chennai

Job description

Career Area: Technology, Digital and Data Job Description: Your Work Shapes the World at Caterpillar Inc. When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it. Summary: As a MLOps engineer, you will be responsible for deploying and maintain the full lifecycle of applications and systems that utilize AI to improve performance and efficiency, including but not limited to deep learning, neural networks, chatbots, natural language processing. Roles & Responsibilities: - Explore, implement and deploy pipelines for deep learning, neural networks, chatbots, and image processing solutions. - Collaborate with cross-functional teams to deliver high-quality AI projects. - Tracking of multiple models, experiments for auditing purpose - Collaborate with data scientists for hyper parameter tuning and features maintenance - Model management and versioning - Work with infra team, data scientists, business in establishing artifact lineage, model registry, governance - Assist in testing, automated deployment - A pipeline for triggering retraining to detect model drift or data drift, trigger retraining - Working knowledge of AWS Lambda, Sagemaker, AWS Step Functions Professional & Technical Skills: - Must To Have Skills: Proficiency in Machine Learning Operations. - Creation of CI,CD Pipelines for ML algorithms, training, prediction pipelines - Work with business, data scientists to ensure value realization, ROI on operationalization of models - Strong understanding of statistical analysis and machine learning algorithms. - Containerization, packaging of ML models - Endpoint creation for prediction - Experience with data visualization tools such as Tableau or Power BI. - Hands-on experience implementing various machine learning algorithms. - Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Skill Descriptors Core Application Systems: Knowledge of major production application systems used for delivery of services to internal and external clients; ability to leverage major production application systems in diverse situations. Level Working Knowledge: • Helps create contingency plans to mitigate impact of disruption on core applications. • Identifies key players, criticalities, roles, and responsibilities. • Investigates application-related issues with both business and IT professionals. • Recommends enhancements for a major application system or related subsystems. • Works with core application systems for a major business unit or function. Problem Solving: Knowledge of approaches, tools, techniques for recognizing, anticipating, and resolving organizational, operational or process problems; ability to apply knowledge of problem solving appropriately to diverse situations. Level Working Knowledge: • Identifies and documents specific problems and resolution alternatives. • Examines a specific problem and understands the perspective of each involved stakeholder. • Develops alternative techniques for assessing accuracy and relevance of information. • Helps to analyze risks and benefits of alternative approaches and obtain decision on resolution. • Uses fact-finding techniques and diagnostic tools to identify problems. Application Design, Architecture: Knowledge of application design and architecture principles and practices; ability to utilize application design methodologies, tools, and techniques to convert business requirements and logical models into a technical application design. Level Extensive Experience: • Analyzes system requirements and translates them into detailed design spe