ML Ops Engineer

Location San Francisco HQ Office Employment Type Full time Location Type Hybrid Department Research & Development, Perception Compensation $174,308 – $226,000 • Offers Equity • Offers Bonus We determine fair compensation for each position by considering market rates, qualifications, experience, and location. This job posting reflects a salary range based on different levels within the position, which are primarily determined by location. Your interview performance will help us determine your base salary offer within this range. Keep in mind that salary is just one piece of Hayden's total compensation package. We also offer equity and a company-wide bonus plan. Additional benefits are shared as part of this job posting. Benefits and Perks There are endless learning and development opportunities from a highly diverse and talented peer group, including experts in a wide range of fields (AI, Computer Vision, Government Contracting, Systems & Device Engineering, Operations, Communications, and more!). Options for medical, dental, and vision coverage for employees and dependents (for US employees) Flexible Spending Account (FSA) and Dependent Care Flexible Spending Account (DCFSA) 401(k) with 3% company matching Unlimited PTO Daily catered lunches in our San Francisco office 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 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. At Hayden AI, we are committed to creating an inclusive and diverse workplace where everyone is treated with respect and dignity. We believe that our differences make us stronger and drive innovation. As an equal opportunity employer, we do not discriminate against any employee or applicant based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other legally protected status. We are dedicated to fostering a work environment that celebrates diversity and ensures that every individual has the opportunity to contribute to our mission and achieve their full potential. #J-18808-Ljbffr