Basic Qualifications

Education Requirements: Bachelor’s of Science in a STEM (Science, Technology, Engineering, Mathematics) related field, plus 8 yrs or Master’s degree plus 6 yrs. Due to the nature of work performed within our facilities, citizenship is required.

Responsibilities for this Position

Key Responsibilities: Model Deployment:  Deploy machine learning solutions into production in diverse environments, ensuring they operate correctly and efficiently. Automation:  Use tools to automate ML workflows and setting up CI/CD pipelines, including data preprocessing, model training, and model serving. Monitoring:  Continuously monitor the performance of machine learning models to detect and fix issues quickly. Collaboration:  Work with data scientists and software engineers to integrate ML models into applications and services. Optimization:  Optimize models and systems for better performance and scalability. Skills You’ll Bring: Expertise in the full life cycle of ML operations, or previously in an ML Ops role. Expertise in distributed version control systems and DevOps tools, such as GitLab, Git, Linux, Docker, Podman, and Kubernetes. Expertise in software development, with an emphasis on Python. Proficiency in cloud computing (Azure, AWS, Google Cloud) Proven experience leading the design, build, and deployment of complex and performant (reliable and scalable) software solutions in production. Experience with ML frameworks like PyTorch for model training and inference. Excellent written and verbal communication abilities. Understanding of validation methods for ML models. Skills in data preparation and corpus filtering using databases like PostgreSQL and MySQL.

Target salary range: USD $148, - USD $165,;This estimate represents the typical salary range for this position based on experience and other factors (geographic location, etc.). Actual pay may vary. This job posting will remain open until the position is filled.