Senior MLOps Engineer

Who you are

You have 5+ years of experience in MLOps or related fields, with a strong background in building and maintaining machine learning infrastructure. You are proficient in Python and have hands-on experience with cloud platforms like AWS. Your expertise includes containerization technologies such as Docker and orchestration tools like Kubernetes, enabling you to deploy and manage scalable ML models effectively.

You thrive in collaborative environments, working closely with Data Scientists, ML Engineers, and Software Engineers to ensure seamless integration of machine learning models into production. Your strong problem-solving skills allow you to tackle complex challenges and optimize ML workflows, ensuring high performance and reliability.

You are familiar with ML lifecycle management tools such as MLflow and have experience with popular machine learning frameworks like TensorFlow and PyTorch. Your ability to communicate technical concepts to non-technical stakeholders makes you an effective team player, fostering a culture of learning and innovation.

Desirable

Experience with CI/CD pipelines and version control systems like Git is a plus. Familiarity with data processing frameworks such as Apache Spark or Airflow can enhance your contributions to the team. You are also open to exploring new technologies and methodologies to improve ML operations and drive efficiency.

What you'll do

As a Senior MLOps Engineer at Hudl, you will be responsible for designing, developing, and maintaining the MLOps platforms that support our data science teams. You will build scalable ML infrastructure that enables the training, deployment, and monitoring of machine learning models at scale. Your role will involve collaborating with cross-functional teams to ensure that ML models are production-ready and deliver actionable insights to professional sports teams worldwide.

You will own the MLOps pipelines, transforming raw data into valuable insights while ensuring the reliability and performance of the systems you build. Your work will directly impact how teams analyze game data and improve their performance, making a difference in the world of sports analytics.

You will also be involved in optimizing existing workflows and identifying opportunities for automation, enhancing the efficiency of the ML lifecycle. By implementing best practices in MLOps, you will contribute to the continuous improvement of our processes and technologies.

What we offer

Hudl provides a supportive and inclusive work environment where you can grow your skills and advance your career. We believe in empowering our employees to take ownership of their work and make a meaningful impact. You will have access to ongoing learning opportunities and resources to help you stay at the forefront of the rapidly evolving field of machine learning.

We offer competitive compensation and benefits, including flexible work arrangements to support your work-life balance. Join us at Hudl, where you will be part of a team that is passionate about using technology to enhance the world of sports.

We encourage you to apply even if your experience doesn't match every requirement. We value diverse perspectives and are committed to building a team that reflects the communities we serve.