About Axiovia Technologies
Enterprise AI for engineering-intensive industries.
Axiovia Technologies builds enterprise-grade AI solutions that help process and manufacturing industries unlock the value trapped in engineering data and industrial operations. Our platform combines visual and language AI to support engineering-document digitization, asset intelligence, operational safety and related industrial workflows.
Turn modern AI methods into working product features.
Working directly with the Lead Engineer and CTO, you will prototype, build and evaluate AI-driven features across large language models, model training and fine-tuning, RAG pipelines, agentic workflows and enterprise data integration. This role suits a self-directed student or recent graduate who can take direction and execute independently.
The work
Key responsibilities
- Prototype, test and deliver AI-powered product features and internal automations using modern AI tools and platforms.
- Train, fine-tune and evaluate machine learning and language models on domain-specific data, tracking accuracy, latency and cost.
- Design and optimize RAG pipelines, including chunking, embeddings and vector retrieval.
- Develop agentic workflows and multi-step LLM pipelines using APIs such as OpenAI, Anthropic or Gemini and appropriate orchestration frameworks.
- Integrate AI components with enterprise data platforms, databases and APIs.
- Use prompt engineering and iterative evaluation to improve accuracy, robustness and cost efficiency.
- Contribute to OCR, detection, segmentation and other computer-vision or document-AI components when required.
- Write clean, documented Python and maintain reproducible experiments, notebooks and scripts in version control.
- Plan and execute assigned work, communicate findings, flag blockers early and incorporate feedback.
- Track relevant AI research and open-source tools and propose practical improvements.
Required
Qualifications and experience
- Currently pursuing or recently completed a bachelor's or master's degree in Computer Science, Engineering, Data Science, AI or a related field.
- Strong Python skills with working knowledge of NumPy, pandas and scikit-learn.
- Understanding of machine learning and deep learning fundamentals with hands-on PyTorch or TensorFlow experience.
- Experience with model training or fine-tuning using technologies such as Hugging Face Transformers or LoRA/PEFT.
- Practical experience building RAG pipelines and using vector databases such as FAISS, Milvus or Pinecone.
- Experience building agentic workflows and integrating LLM APIs.
- Ability to follow direction, work independently and deliver results on time.
- Clear written and verbal communication, including experiment documentation and result presentation.
Preferred
Additional experience
- Experience integrating AI with data platforms, SQL or NoSQL databases and AWS, Azure or GCP.
- Familiarity with LangChain, LlamaIndex, MCP, MLOps or experiment-tracking practices.
- Exposure to OCR, object detection or document-digitization workflows; GitHub projects or published demos are a strong plus.
How you work
Candidate profile
- A self-starter who can take a task from instruction to execution without constant supervision.
- A curious, fast learner who keeps pace with the evolving AI landscape.
- A detail-oriented problem solver who values reproducible, practical results.
- Collaborative and receptive to feedback in a fast-paced startup environment.
The opportunity
What we offer
- Direct mentorship from the Lead Engineer and CTO.
- Production-oriented experience with modern AI tools, models and industrial use cases.
- A research-driven, product-focused culture that values practical impact.
- Flexible working arrangements and a competitive stipend.
- Potential consideration for a full-time position after successful completion of the internship.