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