MLOPS Engineer with GenAI

Found in: Appcast Linkedin GBL C2 - 2 weeks ago

Philadelphia, United States KTek Resourcing Full time

Job Duration: FTE Only

Visa Accept: Open


Summary:

We're looking for a skilled MLOps Engineer to join our team in the USA. You'll be pivotal in building and managing infrastructure and pipelines for our innovative Generative AI applications, collaborating closely with the Generative AI Full Stack Architect. Your expertise in automating ML lifecycles will ensure the efficiency, scalability, and reliability of our Generative AI models in production.


Responsibilities:

Design, develop, and implement MLOps pipelines for generative AI models, covering data ingestion, preprocessing, training, deployment, and monitoring.

Automate ML tasks using tools like GitOps, CI/CD pipelines, and containerization (e.g., Docker, Kubernetes).

Maintain robust monitoring and alerting systems for generative AI models in production, ensuring timely issue resolution.

Collaborate with the Generative AI Full Stack Architect and other engineers to optimize model performance and resource utilization.

Manage cloud infrastructure (e.g., AWS, GCP, Azure) for ML workloads, focusing on cost-efficiency and scalability.

Stay updated on the latest MLOps advancements and integrate them into our platform and processes.

Communicate effectively with technical and non-technical stakeholders about model health and performance.


Qualifications:

Bachelor's degree in Computer Science, Data Science, Engineering, or equivalent.

8+ years of MLOps or related experience in DevOps, data engineering, or ML infrastructure.

Proven experience automating ML pipelines with tools like MLflow, Kubeflow, Airflow, etc.

Expertise in cloud platforms (e.g., AWS, Azure) for ML workloads.

Strong understanding of CI/CD principles and containerization technologies (Docker, Kubernetes).

Familiarity with monitoring and alerting tools for ML systems (e.g., Prometheus, Grafana).

Excellent communication, collaboration, and problem-solving skills.

Passion for Generative AI and its potential across industries.

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