AI Engineer

Job Title: AI Engineer Employment Type: Full-time Location: Remote (Preferred Dallas) About DeepHow DeepHow is a Physical AI platform for industrial manufacturing, pharmaceuticals, and utilities that helps organizations capture expert know-how, turn it into dynamic work instructions, and drive verified execution on the front line. The platform spans knowledge capture and sharing, AI-powered verification through Smart Compare and photo/video validation, and time and motion intelligence through guided workflows, SOP adherence, and real-time execution visibility. DeepHow supports customers from knowledge capture to verified execution, with strategic account expansion often centered on verification, AI-guided workflows, and time and motion intelligence. The Role We’re looking for an AI Engineer to own our AI pipeline end-to-end. You’ll take over our production ML stack, harden it, and ship improvements fast. Day one, your focus is MLOps and production deployment making sure our models are fast, reliable, and cost-efficient at scale. This is a build-and-ship role, not research. If you like turning prototypes into production systems that real users depend on, read on. What You’ll Own Our AI pipeline - ingestion, processing, inference, monitoring Deployment and scaling of LLM, VLM, and speech models in production (GCP) Latency, cost, and reliability optimization across the stack RAG pipelines, prompting, and evaluation frameworks Infrastructure and tooling to accelerate experimentation and shipping Education & Experience Bachelor’s or master’s degree in computer science, Engineering, or a related technical field (or equivalent practical experience) 3–7+ years shipping ML/AI in production Strong Python; fluent in PyTorch or TensorFlow Hands‑on with LLMs - prompting, fine‑tuning, RAG, evals Solid MLOps chops: CI/CD for models, monitoring, cost optimization Experience deploying on GCP or AWS (GCP preferred) Comfort with vector DBs, embeddings, and retrieval systems Startup‑speed execution Nice to Have Video, speech, or multimodal AI experience MLflow, Kubeflow, Airflow, or similar Manufacturing or frontline workforce context Background shipping AI features in a SaaS product Why DeepHow Real AI problems with real users, not demos Direct impact on frontline workers and industrial operations Small team, high ownership, fast cycles Shape the AI roadmap from the ground up #J-18808-Ljbffr