We’re a thriving and agile tech development firm. Simply put, we care. Our team personally cares about our clients and the world around them, and we care about our team’s life-long dreams, aspirations, and career development.

We strongly believe in the power of community. We celebrate diversity in all its forms. Backgrounds, personalities, career paths, languages... you name it. Role OverviewAs a Senior Software Developer with strong Data Engineering and MLOps experience, you design, build, and deliver robust data and machine learning solutions for our clients.

You combine strong software engineering habits with hands‑on experience in data pipelines, cloud environments, automation, model deployment, monitoring, and production‑ready ML systems. You’re comfortable moving between backend development, data engineering, ML lifecycle practices, infrastructure, CI/CD, observability, and technical leadership. You collaborate closely with technical and non‑technical teammates, mentor others, and help teams make sound technical decisions as we deliver enterprise‑grade AI and data solutions.

Design, build, and deliver scalable software, data, and machine learning solutions for client projects Identify solutions to cross‑functional problems using your software development, data engineering, and MLOps experience Design, plan, and implement data pipelines, ML workflows, and supporting cloud or on‑premise infrastructure Build and improve CI/CD pipelines, data pipelines, model deployment workflows, and automation practices Contribute to containerized, virtualized, and cloud‑native environments that support data and ML workloads Support modernization initiatives by improving architecture, testing, deployment, observability, data quality, and maintainability Define, document,



and communicate non‑functional requirements such as performance, reliability, security, scalability, and maintainability Support ML lifecycle practices such as experiment tracking, model versioning, validation, deployment, promotion, rollback, and monitoring Coach colleagues on software development, data engineering, MLOps, and delivery best practices Uphold and strengthen software development guidelines and quality standards Research, test, and implement new techniques, tools, and technologies Advise clients on technical direction, trade‑offs, architecture, data platforms, and ML solution design 5+ years of software development experience, including recent hands‑on experience with data engineering, MLOps, or production ML systems Bachelor’s degree, college degree, certification in a software‑related field, or equivalent experience Intermediate or conversational French at a minimum Strong technical judgment and ability to make pragmatic architectural decisions Experience building or supporting data pipelines, data platforms, or ML deployment workflows Ability to mentor teammates and help raise the quality of technical delivery At least one major cloud platform such as AWS, Azure, or Google Cloud At least one major server‑side programming language such as Python, Java, Node.Js/TypeScript, Go, C#, or similar At least one major data engineering platform such as Databricks, Snowflake, BigQuery,



Microsoft Fabric, or similar Data pipeline orchestration, version control, data validation, feature pipelines, or feature stores ML lifecycle practices such as experiment tracking, model versioning, validation, deployment, promotion, rollback, and monitoring CI/CD pipelines and deployment automation Virtualization and containerization, ideally in a Linux‑based ecosystem Monitoring and observability tooling and services Testing practices such as unit, integration, functional, end‑to‑end, or load testing Modern development methodologies such as Agile, Scrum, XP, Kanban, Shape Up, etc A modern client‑side framework/library such as React, Angular, Svelte, Vue, Remix, or similar Full‑stack web development LLMOps, RAG systems, vector databases, or GenAI application deployment Edge computing, IoT, robotics, industrial systems, or hardware‑adjacent software Technical leadership in client‑facing projects Application security, networking, identity, or compliance considerations Competitive Salary and contribution to your pension plan (RRSP) Flexible schedule of work and choose how you work Wellness and productivity spending account Training 20 min - Initial introductory call with our technical team 90 min - In‑person interview at our office We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. If you would like more information about how your data is processed, please contact us. #

📌 Senior Software Developer, Data & Mlops (Winnipeg)
🏢 Osedea
📍 Winnipeg