Description:

NobleAI is seeking a Machine Learning Engineer (MLOPS) to help deploy models and data using cloud-managed and open-source tools and services.
The role involves working closely with research and engineering teams to design and enable platform features for batch and real-time inferences.
Responsibilities include providing engineering best practices, creating templates, and developing self-service modules to assist research scientists and other ML engineers in automating production deployments.
The engineer will build configurable and scalable software modules to standardize deployments for both batch and real-time requirements.
NobleAI aims to leverage AI and scientific innovation to build a more sustainable world.

Requirements:

Candidates must hold an MSc Degree in Computer Science or a related field.
A solid understanding of machine learning algorithms and techniques is required.
Applicants should have at least 3 years of experience in building and deploying ML systems.
A minimum of 3 years of experience working with Python and MLOps tools, including Docker, Kubernetes, KubeFlow, TensorFlow, PyTorch, Sagemaker, and MLFlow is necessary.
Candidates should have at least 2 years of cloud experience, specifically with AWS or Azure ML Platforms.
A minimum of 3 years of experience in Software Engineering practices such as version control, testing, DevOps (build pipelines, CI/CD), and Python package management is required.
The ability to effectively communicate complex technical details at a high level is essential.

NobleAI offers top-tier health benefits coverage, including medical, dental, vision, disability, and life insurance.
Employees enjoy generous Paid Time Off and Holidays.
The company supports a remote workforce with access to co-working offices.
A 401(k) plan with employer match is provided.
Employees receive an equity package.
There is a performance-based bonus plan in place.
The base salary range for this position is $140k - $180k per year, depending on experience and geographic location.