AI Infrastructure Architect
3 weeks ago
About the Role
">We are seeking a highly skilled DevOps Engineer to join our team at Together AI. As an MLOps engineer, you will develop systems and APIs that enable our customers to perform inference and fine-tune LLMs.
">Key Responsibilities
">- Implement runtime systems that perform inference at scale using AI/ML models from simple models up to the largest LLMs.
- Work closely with engineering, research, and sales on deploying, evaluating, and operating inference systems for both customers and internal use.
- Build and maintain tools, services, and documentation for automation and testing.
- Analyze and improve efficiency, scalability, and stability of various system resources.
- Conduct design and code reviews.
- Participate in an on-call rotation to respond to critical incidents as needed.
Requirements
">- 5+ years experience working on a production level ML training or inference system.
- Bachelor's degree in computer science or equivalent industry experience.
- Strong understanding of the state of the art in machine learning, especially LLMs.
- Experience with DevOps practices like CI/CD, automation, containerization (Docker), and orchestration (Kubernetes).
- Proficiency in cloud platforms like AWS, Google Cloud, or Azure.
- Expertise in programming (Python, Go, etc.) and frameworks for ML (TensorFlow, PyTorch, Scikit-learn).
Compensation and Benefits
">We offer competitive compensation, startup equity, health insurance, and other benefits. The estimated annual salary range for this full-time position is: $160,000-$240,000 + equity + benefits.
">About Together AI
">We are a research-driven artificial intelligence company dedicated to advancing the field of AI through open and transparent systems. Our mission is to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We invite you to join our passionate group of researchers and engineers in building the next generation AI infrastructure.
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