Senior Software Engineer (MLOps)

Summary Posted: Sep 2, 2024 Weekly Hours: 40 Role Number: 200565089 We are looking for a Senior Software Engineer (MLOps) to help us ensure that machine learning models are not only successfully deployed but also maintained and monitored for optimal performance. You will lead all the processes to design, build and manage reproducible, testable, and evolvable ML-powered software. Description Description This role requires a blend of skills in software engineering, machine learning, and operations to ensure the smooth functioning of ML systems in production environments. In this role you will: - Write reusable, testable, and efficient code - Implement model serving solutions to expose models as APIs or batch processes - Manage model versions to ensure traceability and reproducibility - Implement monitoring solutions to track model performance, system health, and other relevant metrics - Set up alerting mechanisms for model failures or performance degradation - Collaborate with machine learning engineers to ensure efficient deployment and scaling of machine learning models Minimum Qualifications Minimum Qualifications Bachelor or above in Software Engineering, Computer Science, Machine Learning, or a related field 6+ years’ experience as a Software Engineer, ML Engineer, MLOps Engineer, or a related field Demonstrated strong Software Engineering skills, with experience of building scalable and resilient systems Experience with model pipeline and registry tools, detecting and preventing model drift, automating model monitoring, and ensuring model accuracy Proficiency in programming languages such as Python, Java or Golang Effective communication skills in written and spoken English Key Qualifications Key Qualifications Preferred Qualifications Preferred Qualifications Bachelor or Master in Software Engineering, Computer Science, Machine Learning Experience in machine learning frameworks such as TensorFlow, PyTorch, AutoGluon, XGBoost or Scikit-learn Experienced in DevOps Tools such as Docker, Jenkins, Ansible, Grafana, Prometheus, Elastic, or Kubernetes Familiar with CI/CD deployment practices Experience with SQL and database systems such as PostgreSQL Experience with building ETL pipeline in data warehouse such as Snowflake Experience with inference optimization Education & Experience Education & Experience Additional Requirements Additional Requirements More