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 energy, focused on capturing expert know-how and driving verified execution. They are seeking an AI Research Engineer to innovate across their AI platform by researching and developing next-generation models and techniques, working closely with product, engineering, and AI teams.

Responsibilities

• Research and development of AI models for industrial knowledge capture, verification, and workflow intelligence
• Experimentation with LLMs, vision-language models (VLMs), speech models, and multimodal systems — including evaluation of open-weight and proprietary models for customer-specific constraints
• Design and evaluation of advanced RAG architectures, agentic workflows, and reasoning systems
• Model training, fine-tuning, and optimization pipelines
• Benchmarking, evaluation, and experimentation frameworks that measure both model quality and business impact
• Assessment of emerging AI techniques and their applicability to DeepHow’s platform and roadmap
• Collaboration with engineering to transition research prototypes into scalable production systems
• Internal research write-ups, technical documentation, and best practices

Skills

• Bachelor's, Master's, or Ph.D. in Computer Science, Machine Learning, AI, or a related technical field — or equivalent practical experience
• 3+ years of experience in AI/ML research, applied AI, or machine learning engineering
• Strong Python skills with deep expertise in PyTorch (or TensorFlow) and the Hugging Face / Transformers ecosystem
• Hands-on experience training, fine-tuning, and evaluating foundation models
• Practical experience with LLMs and VLMs, prompt engineering, RAG systems, and rigorous model evaluation methodologies
• Familiarity with vector databases and embedding systems
• Experience with large datasets and distributed training and inference environments
• Strong grasp of ML fundamentals, deep learning, and modern AI architectures, plus solid experiment design and statistical analysis
• A track record of translating research concepts into shipped product features
• Experience with video understanding, computer vision, speech recognition, or other multimodal AI
• Familiarity with reinforcement learning, agentic systems, or reasoning models
• Experience with MLflow, Kubeflow, Ray, Airflow, or similar ML platforms
• Publications, patents, open-source contributions, or active participation in AI research communities
• Experience deploying AI systems on GCP or AWS
• Background in manufacturing, industrial automation, workforce training, or operational technology
• Experience building AI products in an enterprise SaaS environment

Benefits

• Full-time
• Remote (Dallas preferred)
• Access to cutting-edge AI technologies, hardware, and research opportunities
• High ownership, rapid experimentation, and fast decision-making
• A talented, mission-driven team applying AI to problems that matter
• Influence over the AI roadmap, from research through production

Company Overview