Open Access Technology International (OATI) is seeking highly motivated individuals to join our team of AI Engineers focused on power systems. This is a fantastic opportunity to gain practical experience working on real-world AI applications alongside leading experts in the energy sector.
Our team is tackling critical challenges in electric power system operations using Artificial Intelligence.
Responsibilities:
- Conduct research and development on specific AI problems critical to power system operations, leveraging OATI's vast datasets spanning decades (e.g., forecasting load, wholesale electricity market prices, renewable energy generation; optimizing grid reliability, resiliency, and stability; signature analysis and anomaly detection).
- Design, build, and deploy agentic AI systems using frameworks such as LangChain, LangGraph and related agentic libraries.
- Implement and optimize retrieval-augmented generation (RAG) pipelines ensuring agents can access and incorporate external knowledge sources for grounded, accurate responses.
- Fine-tune and prompt-engineer LLMs for task-specific reasoning, planning and dynamic adaptation.
- Lead the development of enterprise-grade AI platform that integrates advanced generative AI and LLM technologies.
- Design, build and fine-tune large foundation AI models (e.g., LLMs, multimodal models) for the energy domain.
- Develop and deploy agentic AI systems capable of autonomous decision-making and multi-agent collaboration.
- Build and optimize neural network models tailored to use cases in the energy/power systems industry ensuring high performance and scalability.
- Implement and standardize Model Context Protocol based communication to ensure consistent context management across AI models and agents.
- Establish and enforce best practices for MLOps, model monitoring and observability to ensure robust, scalable and maintainable AI solutions
- Develop and implement machine learning models using popular frameworks (e.g., TensorFlow, PyTorch) to analyze and extract meaningful insights from power system data.
- Participate in the full research cycle, including literature review, data exploration, experimentation, analysis and presentation of findings.
- Collaborate effectively with other researchers, engineers and data scientists.
- Contribute to the development and documentation of technical code.
Qualifications:
Education:
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field; PhD preferred.
Technical Skills:
- 3+ years building and deploying AI-powered systems using LLMs, RAG and agentic architectures
- Solid Python programming skills and experience with modern AI/ML libraries.
- Advanced knowledge of LLMs, including fine-tuning, prompt engineering, and evaluation
- Proven experience implementing RAG systems and integrating vector databases or external knowledge stores.
- Proven experience in building and fine-tuning foundation models (e.g., LLMs, vision transformers, multimodal models) for different domains (such as energy, healthcare, finance, etc.).
- Past experience in implementing association rule mining algorithms to uncover patterns and relationships within large and diverse datasets,
- Past experience in building similarity search pipelines using vector representations to enable accurate ranking and retrieval based on multidimensional feature similarity.
- Deep knowledge of agentic AI frameworks and multi-agent system design.
- Proven ability to design and implement multi-agent systems and agent-to-agent communication
- Strong background in neural network architectures, including transformers and other models.
- Strong background in advanced mathematics and statistics for model optimization and validation
- Familiarity of Model Context Protocol and best practices for managing AI model context and state.
- Proficiency in Python and relevant AI/ML frameworks such as TensorFlow or PyTorch.
- Excellent problem-solving skills and ability to communicate complex AI concepts to technical and non-technical stakeholders.
- Strong foundation in machine learning concepts, including algorithms (e.g., deep learning, reinforcement learning) and statistical methods.
- Experience with AI system security, compliance, and ethical AI considerations.
- Knowledge of natural language processing (NLP) pipelines and data engineering.
- Familiarity with conversational AI and chat bot frameworks.
- Familiarity with version control systems like Git.
- Familiarity with SQL and No-SQL database engines is a plus.
Research and Project Experience:
- Experience conducting independent research or working on AI-related projects.
- (For Ph.D. students) A strong publication record demonstrating research experience.
- (For Master's students) Experience conducting independent research or working on AI-related projects.
Other Skills:
- Excellent analytical and problem-solving skills with the ability to tackle complex problems.
- Strong communication skills to present research findings and collaborate effectively within a team
- Ability to work independently and manage time effectively.
- A passion for research and development in the field of AI and a strong interest in the power sector.
Benefits:
- Gain valuable experience working on real-world AI projects with a significant impact on the future of power systems.
- Work alongside leading experts in AI and the energy sector.
- Potential for co-authorship on research publications (depending on contribution).
- Opportunity to develop your research skills and expertise in a rapidly evolving field.
- Be part of a dynamic and collaborative research team working on a critical global challenge.
