Principal AI/ML & Innovation Engineer

• Designing, developing, and deploying advanced machine learning models and algorithms
• Leading research initiatives to explore novel approaches and technologies
• Designing the architecture of AI systems and ensuring scalability, performance, and reliability
• Collaborating with other teams, such as data scientists, software engineers, and product managers
• Providing technical leadership and mentorship to junior engineers
• Overseeing and guiding multiple design review sessions across different projects
• Partnering with the engineering manager and team lead to establish long-term design and implementation strategies
• Leading efforts to incorporate feedback loops and continuous improvement processes
• Leading meetings, ensuring efficient progress tracking, issue resolution, and team coordination
• Creating and delivering high-level presentations and reports to executive stakeholders
• Applying and leveraging data mining, data modeling, natural language processing, and machine learning to extract and analyze information from datasets
• May be involved in the design and development of solutions to complex applications problems, system administration issues, or network concerns

• Bachelor's or master’s degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline
• Typically, 10-15 years’ experience
• Solid understanding of fundamental AI and machine learning concepts, including supervised and unsupervised learning, deep learning, reinforcement learning, natural language processing, computer vision, and statistical modeling
• Proficient in implementing and deploying various machine learning algorithms, such as decision trees, random forests, support vector machines, and neural networks
• Knowledge of popular machine learning frameworks and libraries like TensorFlow, PyTorch, or sci-kit
• Strong 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
• Expertise in deep learning techniques, architectures, and frameworks (e.g., convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), etc.)
• Strong programming skills in Python, Java, or C++
• Proficiency in data visualization tools and techniques
• Familiarity with software engineering principles, version control systems (e.g., Git), testing methodologies, and agile development practices
• Experience in leading research initiatives, publishing research papers, or contributing to open-source projects in AI
• Experience in guiding and mentoring other engineers
• Strong communication skills

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