As an MLOps Engineer at R Systems, you will play a pivotal role in leveraging data science and engineering expertise to design and deploy cutting-edge machine learning solutions. With a focus on operationalizing machine learning models, you will contribute to the development and implementation of MLOps best practices, ensuring seamless integration and performance optimization in production environments.
Job Responsibilities
- Design and Develop Machine Learning Solutions. Utilize your extensive experience in data science and engineering to design, develop, and implement machine learning solutions tailored to client requirements.
- MLOps Engineering. Apply hands-on expertise in MLOps engineering, including proficiency in container technology, Restful API, and various model deployment techniques. Ensure efficient model performance measurement and monitoring in production environments.
- Technical Proficiency. Demonstrate expert proficiency in programming and querying languages, particularly Python and SQL. Utilize your skills in big data processing, leveraging technologies such as Apache Spark and/or Databricks.
- Technology Utilization. Leverage your proficiency in MLOps technologies, including MLFlow, Azure ML services, AutoML, etc., to enhance model deployment and management processes.
- Project Leadership. Showcase your track record of leading projects and cross-functional teams, driving collaboration, and achieving project objectives within specified timelines.
- Problem-Solving and Analytical Thinking. Apply strong problem-solving and analytical thinking skills to address complex challenges and optimize machine learning workflows.
Qualifications
- Experience. Minimum 5 years of experience in data science or engineering roles, with at least 3 years of hands-on professional MLOps engineering experience.
- Education. Bachelor's or Master's degree in Computer Science, Engineering, or related field.
- Skills. Proficiency in modern machine learning techniques, programming languages (Python, SQL), big data processing technologies (Apache Spark, Databricks), and MLOps tools (MLFlow, Azure ML services, AutoML).
- Attributes. Natural sense of urgency, teamwork, and collaboration. Strong problem-solving abilities and analytical thinking.
At R Systems, we foster a dynamic and collaborative work environment, offering opportunities for professional growth and innovation. Join us in revolutionizing digital product engineering and making a meaningful impact across industries. Apply now to be a part of our transformative journey!