Ambient.ai
Software Engineer, AI Infrastructure - LVM Inference & Evaluation
- Confirmed live in the last 24 hours
- $168k–$205k
- Mid level
- Full-time
- Remote · Redwood City
- 2+ yrs exp
- Added 3 weeks ago
About this role
Ambient.ai is seeking a Software Engineer to build and optimize the AI infrastructure that powers their real-time physical security platform. This role involves designing, building, and maintaining systems for inference, evaluation, and continuous model improvement across various AI models including computer vision, LLMs, and multimodal systems. You’ll collaborate with research and product teams to bring cutting-edge AI advancements to production.
What you'll do
- Design and maintain infrastructure for real-time AI workloads.
- Build scalable systems for running machine learning models on large datasets.
- Optimize inference performance for latency, throughput, and cost.
- Develop evaluation harnesses and benchmarking systems to measure model quality.
- Productionize the latest AI advancements in computer vision and related fields.
- Create observability and monitoring tools for production AI systems.
What they're looking for
- Python
- Machine Learning
- Deep Learning
- LLMs/LVMs
- Inference Optimization
- Distributed Systems
- Cloud Infrastructure
- vLLM/Triton Inference Server
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Ambient.ai
Likely interview questions
- Describe your experience designing and building scalable machine learning infrastructure.
- What techniques have you used for inference optimization (e.g., quantization, batching)?