Job Title

Senior Machine Learning Operations Engineer We're seeking an experienced Senior Engineer to join our MLOps team. In this role, you will play a crucial part in designing, developing, and maintaining scalable and reliable machine learning operations pipelines and infrastructure. Design and implement robust MLOps pipelines for model training, evaluation, deployment, and monitoring using industry-standard tools and frameworks Collaborate with data scientists to streamline the model development process and ensure seamless integration with MLOps pipelines. Optimize and scale machine learning infrastructure to support high-performance model training and inference. Contribute to the development of MLOps standards , processes, and documentation within the organization. Mentor and support junior team members in MLOps practices and technologies. Stay up-to-date with the latest trends and best practices in MLOps, and explore opportunities for continuous improvement. About Us : We value the quality of our technical solutions and are passionate about building the right thing, the right way to best solve the problem at hand. But beyond that, we also value our employees' work-life balance and promote a continuous learning culture. We host bi-annual hackathons, have multiple book clubs focused on constant growth, and embrace a hybrid working environment. Responsibilities : Model Training and Deployment : Design and implement robust MLOps pipelines for model training, evaluation, deployment, and monitoring using industry-standard tools and frameworks. Collaboration and Communication : Collaborate with data scientists to streamline the model development process and ensure seamless integration with MLOps pipelines. Infrastructure Optimization : Optimize and scale machine learning infrastructure to support high-performance model training and inference. Process Improvement : Contribute to the development of MLOps standards, processes, and documentation within the organization. Mentorship and Support : Mentor and support junior team members in MLOps practices and technologies. Continuous Learning : Stay up-to-date with the latest trends and best practices in MLOps, and explore opportunities for continuous improvement. Qualifications : Bachelor's or Master's degree in Computer Science, Statistics, or a related field. 5+ years of experience in software engineering, with 2+ years experience in ML. Proficient in Python and at least one other programming language (e.g., Java, Go, C++). Extensive experience with containerization technologies (Docker, Kubernetes) and cloud platforms (AWS, GCP, Azure). Familiarity with machine learning frameworks and MLOps tools. Experience with big data technologies . Strong understanding of CI/CD principles and practices. Preferred Qualifications : Familiarity with model serving frameworks . Knowledge of infrastructure as code (IaC) tools . Experience with monitoring and observability tools . Contributions to open-source MLOps projects or communities . Benefits : We offer a comprehensive benefits package, flexible work options for work-life balance, volunteer time off, and more. Learn more about our benefits here. Commitment to Diversity and Inclusion : As an Equal Opportunity Employer, we value diversity and equality and empower our team members to bring their authentic selves to work daily.