MLOps & Inference Engineer - Deploy, Optimize, Monitor AI

CAMB.AI Ltd.; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Innovative Environment

Growth Opportunities

Competitive Compensation

Job summary

CAMB.AI Ltd. is seeking a Senior ML Infrastructure Engineer to deploy models into production and own the end-to-end serving pipeline. The role emphasizes optimizing inference quality, reducing latency, and controlling costs across diverse models.

You will build robust monitoring for inference, investigate timing anomalies, and create tooling to accelerate deployment from checkpoint to scaled inference, with a focus on GPU scheduling and optimization.

Responsibilities

• Deploying various models to production and owning the process from working checkpoint to performant serving infrastructure.
• Optimizing inference quality and performance in the model serving stack to improve model output quality and detect hallucinations or errors.
• Enhancing latency, throughput, and cost through techniques like custom kernels, cache optimization, GPU scheduling/scaling, and quantization.
• Implementing robust monitoring and incident flagging systems for inference management and investigating timing anomalies or inference failures.
• Creating tooling to enable rapid deployment of new models from checkpoint to scaled inference, optimizing GPU availability.

Job description

CAMB.AI Ltd. is seeking a Senior ML Infrastructure Engineer to deploy models into production and own the end-to-end serving pipeline. The role emphasizes optimizing inference quality, reducing latency, and controlling costs across diverse models.

You will build robust monitoring for inference, investigate timing anomalies, and create tooling to accelerate deployment from checkpoint to scaled inference, with a focus on GPU scheduling and optimization.