Note: The job is a remote job and is open to candidates in USA. DeepHow is a Physical AI platform for industrial manufacturing, pharmaceuticals, and Electronics that helps organizations capture expert know-how. The AI Engineer will own the AI pipeline end-to-end, focusing on MLOps and production deployment to ensure models are fast, reliable, and cost-efficient at scale.

Responsibilities

• 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

Skills

• 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
• Video, speech, or multimodal AI experience
• MLflow, Kubeflow, Airflow, or similar
• Manufacturing or frontline workforce context
• Background shipping AI features in a SaaS product

Company Overview