Staff AI Engineer — Applied Vision & Video Intelligence

Arlo Technologies, Inc.; Milpitas (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Arlo Technologies, Inc. is seeking a Staff AI Engineer for Applied AI to own models behind Arlo's smart features—on-camera detectors, vision-language models, and retrieval layers.

You will ship models end-to-end, from training to production at consumer scale, balancing accuracy with cost and latency in a hands-on role. You will lead data, evaluation, and deployment pipelines, collaborate with product and firmware teams, and mentor engineers while advancing state-of-the-art CV and multimodal

Qualifications

• BS in Computer Science or related field with 8+ years of experience; MS/PhD preferred (or equivalent practical experience).
• 8+ years building production ML/AI systems, with a track record of owning models end to end — problem framing, data, training, evaluation, deployment, iteration.
• Strong computer vision depth: detection, classification, segmentation, tracking, video understanding; shipped CV models in a product.
• 3+ years working with LLMs or VLMs in production — multimodal modeling, prompt and context design, fine‑tuning, evaluation.
• Strong Python + PyTorch; solid distributed systems and cloud fundamentals (AWS, Docker).
• Experience with embeddings and vector search at scale; multimodal or video retrieval strongly preferred.
• Experience shipping LLM agents with tool use, and pragmatic judgment about when not to use an agent.
• Inference optimization knowledge (serving stacks, quantization, batching, GPU performance) and cost/latency tradeoffs.

Responsibilities

• Build, train, and fine‑tune computer vision models for detection, classification, tracking, re‑identification, and video understanding, using real-world customer footage.
• Own our video‑understanding pipeline: frame selection, prompts, grounding, and captioning/scene description quality tuning.
• Adapt models to our domain: SFT, LoRA/QLoRA, distillation into small deployable models.
• Own the data and evaluation loop: labeling strategy, hard‑negative mining, active learning, and offline/online metrics.
• Own the embedding and retrieval stack behind video search: multimodal embeddings, vector index design, hybrid search, and NL queries.
• Build agentic experiences on top of the vision stack: tool calling, memory, guardrails, and tracing for agent runs.
• Keep production inference fast: serving stacks, quantization, batching, GPU utilization, and model routing.

Skills

Python

PyTorch

AWS

Docker

LLMs

VLMs

Vision models

MLOps

Edge inference

Embeddings

Vector search

Education

BS in Computer Science or related field

MS/PhD in ML/CV or related field preferred

Tools

Docker

AWS

Job description

Arlo Technologies, Inc. is seeking a Staff AI Engineer for Applied AI to own models behind Arlo's smart features—on-camera detectors, vision-language models, and retrieval layers.

You will ship models end-to-end, from training to production at consumer scale, balancing accuracy with cost and latency in a hands-on role. You will lead data, evaluation, and deployment pipelines, collaborate with product and firmware teams, and mentor engineers while advancing state-of-the-art CV and multimodal