Software Engineer, Machine Learning

Sitero is a next-generation clinical trial solutions partner, working with more than 200 Pharmaceutical, Biotech, and Institutional Research Organizations globally. We use technology to drive safety, compliance, quality, and efficiency in research and clinical trials, helping customers bring life-changing treatments to market safer and faster. Driven by a mission to advance clinical research through a technology-enabled delivery model, Sitero leverages a deep well of knowledge across Technology, Clinical Operations, Biosafety, and Drug Safety. We are looking for engineers who are versatile, display leadership qualities, and are enthusiastic to take on new problems across the full stack as we continue to push technology forward. Job Title: Software Engineer, Machine Learning Location: Ontario, Canada (Mississauga area preferred) Why Sitero? At Sitero, you will work on projects that have a direct impact on human health. We offer a fast-paced environment where you can switch teams and projects as our business grows. We are an equal opportunity workplace committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. About the Role We are seeking a Software Engineer, Machine Learning to lead the development of next-generation AI technologies that power our clinical trial platforms. In this role, you will sit at the intersection of AI infrastructure, model optimization, and large-scale software engineering. You will be responsible for building scalable data pipelines for AI, optimizing model performance on hardware accelerators, and deploying state-of-the-art Large Language Models (LLMs) and Multi-Modal models that revolutionize how clinical data is processed and analyzed. You will join a collaborative team that addresses unique problems focused on maximizing scientific and real-world impact. You will not only build AI but also embody the future of engineering by using AI to accelerate your own workflows—leveraging the very tools we build and integrate to augment software development practices. Responsibilities AI & ML Infrastructure: Design, develop, and deploy large-scale ML infrastructure and state-of-the-art AI solutions (e.g., LLMs, Multi-Modal models) to enhance clinical trial efficiency and safety. Systems Architecture: Serve as a technical leader for the design of high-throughput, low-latency data pipelines and storage solutions (data loading, caching, vector stores) required for massive datasets. AI-Augmented Engineering: Actively utilize and advocate for AI-assisted development tools (e.g., coding assistants, automated refactoring agents) to accelerate the software development lifecycle, generate boilerplate, write tests, and optimize legacy codebases. Cross-Functional Leadership: Collaborate with clinical operations, product, and research teams to translate complex business requirements into robust engineering solutions. Establish alignment on technical strategy and influence the direction of Sitero’s AI platforms. Mentorship: Mentor engineers across the organization, fostering best practices in distributed systems, ML engineering, and the adoption of AI-native development workflows. Minimum Qualifications Bachelor's degree in computer science, Engineering, or a related technical field, or equivalent practical experience. 8+ years of experience in software development with proficiency in Python, C++, or similar languages. 7+ years of experience leading technical project strategy and optimizing industry-scale ML infrastructure (model deployment, evaluation, fine-tuning). 2+ years of experience with state-of-the-art AI techniques (LLMs, RAG, Computer Vision) and frameworks (PyTorch, TensorFlow, JAX). Demonstrated proficiency in using AI models to augment software engineering practices—specifically using LLMs for code generation, debugging, architectural design validation, and documentation. Experience designing and scaling data infrastructure, including distributed storage systems, data lakes, or high-performance ETL frameworks. Preferred Qualifications Master’s degree or PhD in Computer Science, Artificial Intelligence, or related technical field. Experience with hardware/software to co-design and optimize models for specific accelerators (GPUs, custom silicon). Background in the Life Sciences, Pharmaceutical, or Clinical Research industries. Familiarity with modern data storage formats (Parquet, ORC) and vector database technologies. Proven track record of technical leadership in a complex, matrixed organization, managing cross-functional projects.