As an AI/ML Ops Engineer, you will architect and operate ML pipelines, automate CI/CD processes, and collaborate with cross-functional teams to enhance engineering productivity.
We are an MIT-born, venture-backed Silicon Valley startup building a real-life 'Jarvis'—an AI Copilot for design and manufacturing. Our goal is to utilize advanced AI, physics simulation, and computer graphics to reduce costs and improve engineering productivity across all steps of the design and manufacturing process.
Responsibilities
- Architect, build, and operate end-to-end ML pipelines for training, validation and deployment on Google Cloud.
- 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.
What we're looking for
- 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, and Google Cloud.
- Deep understanding of large language models (LLMs) and prompt-engineering best practices.
- Experience designing and maintaining CI/CD pipelines to fine-tune or train LLM 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
- Python, TypeScript
- Protobuf, gRPC
- Next.JS, React.JS
- GitHub Actions
- Docker, Kubernetes, Spinnaker
- PostgreSQL
Top Skills
Docker
Github Actions
GCP
Grpc
Kubernetes
Next.Js
Postgres
Protobuf
Python
React
Terraform
Typescript
Similar Jobs
Software
The role involves developing AI-driven features for observability tools, collaborating with cross-functional teams, and delivering scalable solutions.
Top Skills:
AIAWSAzureDockerGCPGenaiKubernetesLlmTerraform
Software • Defense
The Staff Software Engineer leads multi-sprint initiatives, improves system quality, drives technical direction, and mentors peers in a collaborative, async environment.
Top Skills:
AWSCi/CdKubernetesNode.jsPostgresReactRedisTypescript
Software • Defense
The Design Engineer at Onebrief collaborates with product and engineering teams to create user-friendly prototypes and systems, improving operational planning for military users.
Top Skills:
Ai-Powered ToolsAPIsCodeFigma
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
