Staff Software Engineer, AI Inference About Syllo Syllo is on a mission to transform litigation. Our product is a unified litigation platform that enables lawyers and paralegals to safely harness the power of language models and agentic AI throughout the litigation life cycle. Since going to market, we have gained a diverse group of enterprise customers, including some of the biggest law firms and corporations in the country, and we are quickly expanding. By reducing the expense of litigat
Skills in this role
- AI fundamentals
- Machine learning
- MLOps
What the employer asks for
- Salary Range ($190- $230K) plus health insurance and equity.
- United States - Remote Pay Range
- $190,000 - $230,000 USD
Courses relevant to this posting
Relevance is based on skills and concepts — not a guarantee that you qualify.
- Infrastructure Design for AI Systems Covered skills: AI fundamentals Machine learning MLOps Skills to close: None listed
Build the skills for this job
Coming-soon courses matched to this posting — outline, waitlist, and skill path.
Infrastructure Design for AI Systems
7 chapters · 31 lessons
1. Workload Patterns and Capacity Planning
4 lessons
Distinguish training, inference, and retrieval workloads and map each to infrastructure requirements.
2. The AI Infrastructure Stack
5 lessons
Navigate the layered architecture from facilities to serving and understand interdependencies.
3. Inference Serving Architecture
5 lessons
Design systems that deliver model outputs with predictable latency and cost.
4. Retrieval-Augmented Generation Pipelines
4 lessons
Build systems that combine external knowledge with model inference for grounded responses.
5. Compute Sourcing and Deployment Models
5 lessons
Evaluate options for acquiring and deploying compute capacity based on business constraints.
6. Observability, Security, and Governance
4 lessons
Instrument AI systems for monitoring, access control, and regulatory compliance.
7. Infrastructure Decision Frameworks
4 lessons
Apply structured methods to evaluate infrastructure choices for real-world AI projects.
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