Lead Software Engineer - AI

Lead Software Engineer - AI

Job-Specific Responsibilities: Develop production-ready software solutions that solve real business problems, considering business needs and technology/operations landscape; lead interaction with internal stakeholders and technology on specific projects and initiatives Apply software engineering, data science, machine learning, and AI techniques to derive business value from the full range of internal and external data, leveraging Cloud-based technology Design solutions, build initial code, and provide documentation with ways of working to minimize time to value and maximize re-usability Translate complex data and methodology into strategic, operationally feasible insights and recommendations; automate implementation Communicate clearly and effectively to technical and non-technical audiences, verbally and visually, to create understanding, engagement, and buy-in Identify trends and opportunities to drive innovation, both in what we do and how we do it; evaluate new software engineering, data science, machine learning, and AI technologies and tools that can boost team performance, innovation, and business value Manage, coach, and mentor a team of software engineers and data scientists, serving as a predominant technical expert Actively contribute to and re-use community best practices Build trust and collaboration by being present on-site and engaging directly with colleagues and various constituents. This role is responsible for other duties as assigned. Qualifications

Basic Qualifications: Minimum of seven years’ post-secondary education or relevant work experience Additional Qualifications and Skills: Required skills Bachelor’s/Advanced Degree in Mathematics, Physics, Computer Science, Engineering, Statistics, or 7+ years equivalent work experience 3-5 years of experience in developing a variety of software products in a commercial environment 2+ years of experience in building generative AI-based products. Strong Python and Typescript/JavaScript skills required; Expertise in multivariate statistical modelling (e.g., clustering, regression, principal components and factor analysis, time-series forecasting, Bayesian methods) and modern machine learning (ensemble methods, regularization, gradient boosting, representation learning, deep neural networks, transformers architectures, self-supervised learning, and MLOps fundamentals) required Experience with cloud computing platforms (AWS, GCP, or other), or equivalent on-premise platform Experience working in agile methodology is required Prior experience in leading data science and machine learning based software development projects

focused on solving business problems and seizing business opportunities Desired skills Proficiency in SQL desirable Ability to mentor and lead others; provide hands-on technical guidance; conduct code reviews Ability to simultaneously coordinate and track multiple deliverables, tasks, and dependencies across multiple stakeholders / business areas Experience with deep learning and neural network architectures (e.g., CNNs, RNNs, transformers), including generative and self-supervised models, and with frameworks such as TensorFlow or PyTorch is desirable. Proficiency with data visualization tools is desirable