Artificial Intelligence and Machine Learning Graduate

• We are looking for passionate graduates to join our R&D team
• In this role, you will help develop AI capabilities into our existing suite of products or help build AI-enabling platform services and public APIs that are secure, reliable, and cloud-native
• These services will act as foundational building blocks for AI adoption across AVEVAs product portfolio and partner ecosystem
• You will part of a Scrum team to build innovative, standards-compliant, secure and production-grade AI capabilities, with a builder mindset - rapid prototyping and continuous improvement with agility of a start-up

Key Responsibilities:

• Collaborate with cross-functional teams to design, develop, and deploy machine learning models and AI solutions for real-world problems
• Assist in data collection, preprocessing, and exploratory data analysis to ensure high-quality datasets for model training and evaluation
• Implement, test, and optimize machine learning algorithms using relevant libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn
• Contribute to the development and refinement of AI pipelines, including data ingestion, feature engineering, model selection, and validation
• Conduct literature reviews to stay updated on the latest trends, techniques, and developments in the field of AI and machine learning
• Document technical processes, experiments, and results to facilitate knowledge sharing and reproducibility within the team
• Participate in code reviews, brainstorming sessions, and team meetings to foster a collaborative and innovative working environment
• Present findings, analyses, and results effectively to both technical and non-technical stakeholders
• Desired Skills and Knowledge in AI/ML:Solid understanding of foundational AI and machine learning concepts, including supervised and unsupervised learning, classification, regression, clustering, and model evaluation
• Familiarity with algorithms such as linear regression, logistic regression, decision trees, support vector machines, neural networks, and ensemble methods
• Proficiency in programming languages commonly used in AI/ML, such as Python or R, along with experience using relevant libraries (e g , NumPy, pandas, scikit-learn, TensorFlow, PyTorch) Knowledge of C# and Net would be an advantage
• Knowledge of data preprocessing techniques, feature selection, and dimensionality reduction
• Basic experience with data visualization tools and techniques to communicate insights from data
• Understanding of deep learning architectures particularly transformer models, and foundational knowledge of Large Language Models (LLMs) and generative AI concepts
• Familiarity with prompt engineering techniques for interacting with generative AI models and basic knowledge of RAG (Retrieval Augmented Generation) architectures
• Awareness of emerging AI interoperability standards, such as Model Context Protocol (MCP) and Agent2Agent (A2A), and their role in building interconnected AI systems
• Ability to work with version control tools such as Git, and familiarity with collaborative development practices
• Strong problem-solving skills, analytical thinking, and attention to detail
• Excellent written and verbal communication skills
• Prior internships, coursework projects, or research experience in AI/ML is a strong plus.