ML Ops Engineer
- Massachusetts
- onsite
- Full time
$120,000–$160,000 / yearPosted
Free to apply. You’ll finish on the employer’s own site.
Skills mentioned
- Google Cloud
- AWS
- CI/CD
- GitHub
- Prometheus
- Python
+6 more
- Docker
- Kubernetes
- Terraform
- Machine Learning
- TypeScript
- Next.js
Requirements:
BS in Computer Science or a related field.
5+ years of experience as a AI/ML Ops, DevOps, Infrastructure Engineer or equivalent.
Expert-level Python and TypeScripts skills.
Experience with Docker, Kubernetes, Terraform, Google Cloud and AWS.
Deep understanding of machine learning models, including LLMs.
Experience designing and maintaining CI/CD pipelines to fine-tune or train ML models.
Excellent written and verbal communication skills.
Bonus Points
Experience in computer graphics or physics-based simulation.
Background in setting up Prometheus/Grafana, ELK, or similar monitoring stacks.
Experience with Vertex AI.
Experience working with custom Domain-Specific Languages.
Our tech stack
Google Cloud, AWS
Python, TypeScript
Protobuf, gRPC
Next.JS, React.JS
GitHub Actions
Docker, Kubernetes, Spinnaker
PostgreSQL
- Architect, build, and operate end-to-end ML pipelines for training, validation and deployment on Google Cloud and AWS.
- Define, instrument, and maintain logging, monitoring, and alerting for model performance and data drift.
- Automate CI/CD for ML artifacts and infrastructure using GitHub Actions or equivalent.
- Collaborate with cross-functional teams, including frontend engineers, backend engineers, research engineers, and infrastructure engineers.
- Write clean, well-documented, fast, and maintainable code.
- Help ensure our systems have high availability and performance.
- Experience in computer graphics or physics-based simulation.
- Background in setting up Prometheus/Grafana, ELK, or similar monitoring stacks.
- Experience with Vertex AI.
- Experience working with custom Domain-Specific Languages.
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