Machine Learning Operations Engineer
Posted 684 days ago, which is unusual. The employer's own board was still carrying it when we last read it, 2 hours ago.
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 4h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 684d ago
The date the source published, not the day we noticed it (2024-11-25). Last seen at its source 2h ago.
We have tracked this listing since 7 Oct 2026 (3 days). The employer's own board has carried it every time we have read it, most recently 2 hours ago.
Is it remote?
Remote
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
Not stated
The description states no restriction of its own. This is the source's own tag.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Greenhouse employer's own board first seen 3d ago · last seen 2h ago
The listing
Job Description
Join Buzz Solutions and be part of a dynamic team that is shaping the future of energy and technology. If you are passionate about delivering exceptional customer support and thrive in a collaborative and innovative environment, we want to hear from you! Apply now to embark on an exciting journey with us.
Responsibilities
- Build and maintain the infrastructure needed to support machine learning development and deployment.
- Develop REST API and gRPC applications using Python for deploying models as APIs.
- Build end-to-end pipelines for model inference, backend and data on the cloud software platform.
- Integrate SQL and NoSQL database systems with the software platform.
- Work with model registries and MLOPs frameworks to deploy machine learning models
- Setup tools and metrics to monitor, analyze drift and maintain machine learning models in production.
- Develop and maintain CI-CD pipelines to deploy ML based backend artifacts.
- Monitor the logs of customer usage of the products and test for any vulnerabilities.
- Containerize ML based backend applications and deploy container images on Kubernetes engine.
- Maintain cloud infrastructure including Kubernetes engine and virtual machines on Google Cloud Platform.
- Design and deploy cloud infrastructure, database systems and optimize performance and costs.
- Provide unit and stress testing frameworks for cloud infrastructure services deployed in production environments.
- Document the process, code reviews and workflow to streamline product development and enhancements.
- Establish AI based software platform features and timelines for product roadmap.
- Review the process and product performance data w/ team to develop standard work.
- Suggestion optimal and current technological stack for building out the elements of the ML-based software platform backend.
- Work with a team of software engineers to enhance the performance of the software platform and run continuous unit tests for deployed products.
Qualifications & Experience
- The candidate must have a bachelor’s degree in computer science or related field and 5 years of experience, including:
- Designing, implementing, debugging web technologies and server architectures
- Coding, testing and developing using Python
- Experience in SQL and NO SQL databases in Cloud Infrastructure
- Experience in developing backend applications, API integrations, data pipelines on cloud infrastructures to handle customer data
- Utilizing and maintaining cloud infrastructure and services of using Google Cloud/AWS/Azure Cloud
- Employer will accept a master’s degree and 3 years’ experience in lieu of the Bachelor’s plus 4.
*Buzz Solutions does not provide sponsorship for work authorizations in the United States at this time*