AI and Machine Learning Engineer

• Design, develop, and implement machine learning models and algorithms
• Prepare and pre-process large datasets for machine learning tasks
• Train machine learning models using appropriate algorithms and frameworks
• Collaborate with cross-functional teams
• Contribute to design review sessions
• Deals with real-world datasets
• Provides feedback to peers
• Contribute to stand-up meetings
• Prepare comprehensive presentations and reports
• Interpret and report data findings
• Maintain or update specific business intelligence tools, databases, dashboards, systems, or methods

• Bachelor's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline
• Master’s degree is desirable
• Typically, 2-4 years’ experience
• A solid understanding of mathematics, including linear algebra, calculus, and probability theory
• Proficiency in programming languages such as Python, R, or Java
• Knowledge of relevant libraries and frameworks like TensorFlow, PyTorch, scikit-learn, or Keras
• Experience with SQL for data manipulation and database querying
• Understanding of GitHub CoPilot, Cursor, N8N, vibe coding, Windsurf, and similar technologies
• Experience in Cloud Infrastructure (AWS, Azure, etc)
• Knowledge of Open Source, Linux, etc
• Understanding of Devops, SRE
• Hands-on experience in developing and implementing machine learning models
• Practical experience with data cleaning, data pre-processing techniques, and feature engineering
• Experience designing and developing machine learning models using algorithms such as linear regression, deciding trees, random forests, support vector machines, or deep learning models
• Familiarity with model evaluation techniques, hyperparameter tuning, and cross-validation
• Proficiency in software engineering principles and practices
• Experience with version control systems (e.g., Git), software development methodologies, and deploying machine learning models in production environments
• Strong communication skills, both technical and non-technical

Artificial Intelligence Technologies, Cross Domain Knowledge, Data Engineering, Data Science, Design Thinking, Development Fundamentals, Full Stack Development, IT Performance, Machine Learning Operations, Scalability Testing, Security-First Mindset

• Health & Wellbeing
• Personal & Professional Development
• Unconditional Inclusion