Overview
Full Time
Skills
Java
MLOps
Job Details
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 ML 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 ML 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, Google Cloud Platform, Azure) for ML
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 ML infrastructure.
Proven experience in 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 like
Docker and Kubernetes.
Familiarity with monitoring and alerting tools for ML 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.
Band 4C:
Senior individual contributor with significant expertise and leadership experience.
Manages complex projects and initiatives with independent decision-making
authority.
Provides technical guidance and mentoring to junior team members.
Has a proven track record of success in delivering impactful results.
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 ML 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 ML 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, Google Cloud Platform, Azure) for ML
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 ML infrastructure.
Proven experience in 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 like
Docker and Kubernetes.
Familiarity with monitoring and alerting tools for ML 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.
Band 4C:
Senior individual contributor with significant expertise and leadership experience.
Manages complex projects and initiatives with independent decision-making
authority.
Provides technical guidance and mentoring to junior team members.
Has a proven track record of success in delivering impactful results.