AI/ML Engineer Work on cutting-edge technologies like Natural Language Processing (NLP), Generative AI, and Large Language Models (LLMs) Assist in building intelligent systems for real-world applications Collaborate with data scientists and product teams on end-to-end ML workflows Cloud DevOps Engineer Get hands-on with AWS, Azure, or GCP cloud platforms Automate infrastructure, CI/CD pipelines, monitoring, and deployments Learn Infrastructure as Code (IaC) using tools like Terraform or Cloud Formation Software Engineer (Backend/Frontend)
Build scalable applications using Python, Node.js for backend and React.js for frontend Contribute to the full-stack development lifecycle Participate in design, coding, testing, and debugging of software components MLOps Engineer Automate and scale ML workflows from development to production Work with tools like MLflow, Kubeflow, Docker, Kubernetes Ensure reproducibility, monitoring, and performance of ML models in production
Data Engineer Develop robust ETL pipelines, data ingestion, and transformation logic Work with databases, data warehouses, and data lakes Handle real-time and batch data workflows using tools like Apache Airflow, Spark, Kafka
Job Classification
Industry: Software Product Functional Area / Department: Data Science & Analytics Role Category: Data Science & Machine Learning Role: Machine Learning Engineer Employement Type: Full time