Machine Learning Data Engineer at Pennsylvania - EST/CST - Candidates only - 3-4 day need to be onsite in a month. Summary: We are seeking a highly skilled and experienced MLOps Engineer to join our team in USA. You will play a crucial role in building and maintaining the infrastructure and pipelines for our cutting-edge Generative AI applications, working closely with the Generative AI Full Stack Architect . Your expertise in automating and streamlining the Client lifecycle will be instrumental in ensuring the efficiency, scalability, and reliability of our Generative AI models in production. Responsibilities:
- Design, develop, and implement MLOps pipelines for generative AI models, encompassing data ingestion, pre-processing, training, deployment, and monitoring.
- Automate Client tasks across the model lifecycle, leveraging tools like GitOps, CI/CD pipelines, and containerization technologies (e.g., Docker, Kubernetes).
- Develop and maintain robust monitoring and alerting systems for generative AI models in production, ensuring proactive identification and resolution of issues.
- Collaborate with the Generative AI Full Stack Architect and other engineers to optimize model performance and resource utilization.
- Manage and maintain cloud infrastructure (e.g., AWS, GCP, Azure) for Client workloads, ensuring cost-efficiency and scalability.
- Stay up-to-date on the latest advancements in MLOps and incorporate them into our platform and processes.
- Communicate effectively with technical and non-technical stakeholders about the health and performance of generative AI models.
Qualifications:
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related field, or equivalent experience.
- 8+ years of experience in MLOps or related areas, such as DevOps, data engineering, or Client infrastructure.
- Proven experience in automating Client pipelines with tools like MLflow, Kubeflow, Airflow, etc.
- Expertise in cloud platforms (e.g., AWS, Azure) for Client workloads.
- Strong understanding of CI/CD principles and containerization technologies like Docker and Kubernetes.
- Familiarity with monitoring and alerting tools for Client systems (e.g., Prometheus, Grafana).
- Excellent communication, collaboration, and problem-solving skills.
- Ability to work independently and as part of a team.
- Passion for Generative AI and its potential to revolutionize various industries.