Bright Vision Technologies is seeking a skilled Model Serving Engineer to join their dynamic team and contribute to their mission of transforming business processes through technology.
Requirements
- Design and operate model serving platforms supporting diverse workloads
- Optimize inference performance using continuous batching, paged attention, speculative decoding, and request multiplexing
- Implement multi-tenant routing, rate limiting, and quality-of-service policies across model endpoints
- Build autoscaling and capacity management systems that balance latency, throughput, and cost
- Tune GPU utilization, memory management, and KV cache strategies for LLM serving workloads
- Integrate model serving with API gateways, identity systems, and observability platforms
- Implement caching, prompt deduplication, and response reuse strategies where appropriate
- Drive end-to-end observability including latency histograms, queue dynamics, GPU utilization, and error tracking
- Develop deployment workflows including canary releases, shadow testing, and automated rollback
- Operate incident response for high-availability AI services and drive durable reliability improvements
- Collaborate with ML and product teams to support new model releases and capability rollouts
- Implement security controls including request signing, content filtering, and abuse detection at the serving layer
- Document operational procedures, performance characteristics, and tuning guidance for internal teams
- Stay current with AI serving research and translate advances into production capabilities
- Six or more years of experience in distributed systems, infrastructure, or ML platform engineering
- Strong proficiency in Python and a systems language such as Go, Rust, or C++
- Deep experience operating high-throughput, low-latency services in production
- Hands-on experience with LLM or large model inference frameworks such as vLLM or TensorRT-LLM
- Strong understanding of GPU architecture, memory hierarchies, and accelerator utilization
- Familiarity with Kubernetes, autoscaling, and modern cloud platforms
- Experience with observability stacks including metrics, tracing, and structured logging
- Solid grounding in performance engineering and capacity planning
- Strong communication and incident response skills
Benefits
- Competitive base salary
- Plus benefits
