MLOps Engineer

We are looking for a MLOps engineer to join the manufacturing AI team and help us shape our machine learning solutions, production test predictions, yield forecasting, quality control methodologies and anomaly detection across the manufacturing process.As a MLOps Engineer, you will play a meaningful role in bridging the gap between machine learning and software engineering. Your primary responsibility will be to develop, deploy, and maintain the infrastructure and workflows required for the end-to-end machine learning lifecycle. If you are genuinely passionate about machine learning operations and possesses excellent problem-solving, we'd love to hear from you!What you’ll be doing:Collaborate with multi-functional teams, including data scientists, data engineers, and DevOps, to craft, implement, and maintain scalable ML infrastructure and workflows.Develop and implement deployment strategies for machine learning models, ensuring efficient and reliable model serving in manufacturing production environments.Automate and streamline the ML workflow, including data ingestion, feature engineering, model training, and model evaluation, using industry's gold standard methodologies, frameworks, and tools.Build and maintain scalable data pipelines, ensuring efficient data storage, retrieval, and transformation for ML use cases.Monitor and optimize ML systems for performance, scalability, and reliability.Implement and maintain CI/CD pipelines for ML projects, enabling continuous integration, deployment, and monitoring of ML models.What we need to see:Bachelor’s or master’s degree in computer science, Engineering, or a related field.+3 years of experience as a MLOps Engineer or in a similar role, working on deploying and leading machine learning models in production environments.Strong programming skills in languages such as Python, Java, or Scala, with experience in building scalable and efficient systems.Experience with containerization technologies like Docker and orchestration tools like Kubernetes.Knowledge of data engineering concepts and technologies, including data pipelines, ETL processes, MongoDB and SQL.Ways to stand out from the crowd:Strong problem-solving and analytical skills, with the ability to handle complex technical challenges and provide innovative solutions.Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and their deployment.Experience working and data engineering frameworks such as Kafka, Spark, Airflow or Hadoop.Self-motivated with a goal to stay updated on the latest methodologies and machine learning operations technologies.Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.