ML Ops Engineer

About Us At Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges. From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future. About the Role As a MLOps Engineer within the Perception Deep Learning team, you will lead the design and evolution of our machine learning platform, enabling teams to build, deploy, and scale intelligent systems with reliability and speed. In this role, you will partner closely with perception, deep learning and platform engineers to build infrastructure to train and operationalize machine learning models and drive best practices across the ML lifecycle. You will play a key role in shaping the architecture of our ML infrastructure, from data ingestion and training pipelines to deployment, monitoring, and governance. As a senior member of the team, you will influence technical strategy, mentor engineers, and champion a culture of reproducibility, observability, and continuous improvement.. This position is based in and follows a hybrid schedule with at least 3 days in-office per week. Key Responsibilities Below are your primary responsibilities — these represent the core areas where you’ll make an impact. As part of a rapidly evolving team, we look forward to your impact expanding over time. Design, deploy and maintain cloud based workflows to ensure efficient deployment and management of AI models. Collaborate with cross-functional teams to identify bottlenecks and implement solutions to improve workflow efficiency Ship new features and updates rapidly, maintaining a high level of quality and reliability. Implement cost-saving strategies to minimize infrastructure expenses while maximizing performance. Stay informed with the state of the art tools and technologies in the domain of MLOps and implement them for making the ML workflows more efficient and effective. Participate actively in the team's software development process, including design reviews, code reviews, and brainstorming sessions. Keep software development documents accurate and updated. Key Qualifications Bachelors Degree with 3-4 years of experience or a Masters Degree with 2 years experience in Computer Science, Electrical Engineering, or a related field. Core Skills: General Software Engineering skills with 3+ years of programming experience in python and the surrounding tooling ecosystem along with familiarity in linux and expertise in infrastructure, cloud and/or MLOps Personal Attributes: Team player, good communication skills, self starter. Strong teamwork and communication skills to collaborate with cross-functional teams, including ML and software engineers. Nice to Have: Experience building MLOps pipelines for deep learning based perception solutions on AWS or GCP

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