Full Time
$2,000 - $2,500 DOE
40
May 29, 2024
Company Overview: Quibble is a leading revenue management company that is revolutionizing the way we use machine learning to drive business growth. We are seeking a highly skilled and motivated ML Ops Engineer to join our team and play a crucial role in deploying and managing our machine learning models at scale. Job Responsibilities: - Design, build, and optimize data pipelines using AWS to extract, transform, and load data from various sources into our data lake and data warehouse. -Work closely with data scientists and analysts to understand their requirements and translate them into efficient data processing workflows. -Develop and maintain data processing applications using data frames (e.g., Pandas, Spark DataFrame) to perform complex transformations and aggregations. -Implement best practices for data governance, data quality, and metadata management to ensure the reliability and accuracy of our data. -Collaborate with cross-functional teams to integrate machine learning models into production systems and automate model deployment using ML Ops tools and frameworks. -Monitor performance metrics, troubleshoot issues, and optimize the performance of data pipelines and machine learning workflows. Qualifications: - Strong background in AWS infrastructure. - Experience with ML tools and frameworks such as TensorFlow, PyTorch, or scikit-learn. - Proficiency in query optimization. - Solid understanding of cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). - Familiarity with DevOps principles and practices. - Excellent problem-solving and communication skills. - Ability to work independently and collaborate effectively in a team-oriented environment. Benefits: - Competitive compensation. - Opportunity to work with cutting-edge technologies. - Career growth and development opportunities.