About Us
At Hayden AI, we are on a mission to harness the power of artificial intelligence and machine learning to transform the way governments and businesses address real-world challenges. From optimizing bus lane and bus stop enforcement to pioneering digital twin modeling and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive forward a sustainable future.
What the job involves
Hayden AI seeks an ML Ops engineer to support the company’s deep learning team in revolutionizing public transit. As an MLOps Engineer, you'll play a critical role in optimizing orchestration processes, reducing costs, upgrading throughput, and ensuring fast and efficient project delivery. You'll work closely with our engineering and data science teams to streamline our machine learning operations pipeline and implement best practices for managing and deploying our vision AI models.
Responsibilities:
Optimize orchestration processes to ensure efficient deployment and management of AI models.
Implement cost-saving strategies to minimize infrastructure expenses while maximizing performance.
Upgrade throughput to enhance the scalability and responsiveness of our AI systems.
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.
Deploy and monitor machine learning models produced by deep learning engineers.
Design, deploy, and maintain performant and scalable processes to acquire and manipulate data and make datasets more easily accessible to the team.
Participate actively in the team's software development process, including design reviews, code reviews, and brainstorming sessions. Keep software development documents accurate and updated.
Qualifications:
5+ years of programming in one or more languages (Go, Python)
Strong experience with TensorRT and PyTorch, including optimizing and deploying machine learning models for production environments.
Ability to design, implement, and manage CI/CD pipelines that connect to real hardware, ensuring automated and reliable model deployment and updates.
BS or MS in Computer Science, Electrical Engineering, or a related field.
Proven experience in deploying machine learning models on physical devices, ensuring seamless integration and performance in real-world applications.
Demonstrated expertise in troubleshooting and optimizing both software and hardware systems to support efficient ML model deployment.
Strong teamwork and communication skills to collaborate with cross-functional teams, including data scientists, software engineers, and hardware specialists.
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
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. Please do not forward resumes to our jobs alias, Hayden AI employees or any other company location.
Hayden AI is not responsible for any fees related to unsolicited resumes.Compensation Range: $145K - $171K
