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

1. 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.
2. 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.
3. 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.
4. Technology Utilization. Leverage your proficiency in MLOps technologies, including MLFlow, Azure ML services, AutoML, etc., to enhance model deployment and management processes.
5. Project Leadership. Showcase your track record of leading projects and cross-functional teams, driving collaboration, and achieving project objectives within specified timelines.
6. Problem-Solving and Analytical Thinking. Apply strong problem-solving and analytical thinking skills to address complex challenges and optimize machine learning workflows.

Qualifications

1. Experience. Minimum 5 years of experience in data science or engineering roles, with at least 3 years of hands-on professional MLOps engineering experience.
2. Education. Bachelor's or Master's degree in Computer Science, Engineering, or related field.
3. 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).
4. 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!