Hace 1 sem
Senior MLOps Engineer
$65,000 - $75,000 Mensual
Sobre el empleo
Detalles
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Tiempo completoEspacio de trabajo:
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Senior MLOps Engineer
B2+ Senior
Time Zone: The candidate should be available to work till 1 pm PST
Duration: from 3-6 months with possible extension
Description:
The Senior Machine Learning Engineer will work in the MLOps Initiative within the project, enabling AI-driven R&D
We aim to standardize and implement tools to enable ML Scientists with streamlined capabilities to develop and deploy models.
Our initiative will develop strategic and holistic solutions by partnering with our scientific stakeholders to bring their modeling work to the cloud and provide MLOps solutions to streamline model creation to inference/monitoring.
Major responsibilities:
· Design, enhance, scale, and maintain machine learning solutions from conception to deployment in a production environment.
· Collaborate with MLOps Initiative engineering and product management to translate scientific and technical requirements into scalable ML systems.
· Architect MLOps pipelines using orchestration frameworks to streamline data preparation, training, deployment, and machine learning model lifecycles.
· Contribute to machine learning architecture to support scalable and repeatable model training and deployment.
· Design and implement robust continuous monitoring systems for deployed models to track performance, data drift, and anomalies to enable model retraining.
· Facilitate the creation of automated processes for model validation and testing.
· Ensure best practices in code quality, version control, and CI/CD for data and machine learning pipelines.
· Work with computational scientists to understand and leverage domain specific software libraries and frameworks.
· Perform code review and refactoring to ensure high-quality software
· Write technical documentation.
Requirements and skills:
· Expertise with cloud services and containerization technologies/platforms, particularly AWS and Kubernetes.
· Hands-on experience in the orchestration and optimization of scaled ML pipelines on Kubernetes.
· Expertise in ML frameworks (e.g., TensorFlow, PyTorch/Lightning), programming languages (Python), MLOps technologies (e.g., Weights & Biases, AWS Sagemaker, Ray), and job scheduling frameworks (e.g., Slurm, AWS Step Functions)
· Proficient with software engineering best practices, including agile development, code reviews, build processes, testing, and operations
Experience with distributed computing and big data technologies (e.g., Batch, Ray, Spark)
· Familiarity with distributed training systems
· Familiarity with Large Language model development is a plus.
· Effective in communication, teamwork, and critical thinking.
· Degree in Computer Science, Statistics, or relevant field.
ID: 19280713