Artificial Intelligence Engineer
PrivateAI is an AI protocol to store, process, validate and sell your data assets. PrivateAI will generate datasets for you from any unstructured data you provide.
Funding
Projects
About PrivateAI
PrivateAI is an AI protocol to store, process, validate and sell your data assets. It generates datasets from unstructured data, using semantic models to ensure they are machine learning ready. The PrivateAI ecosystem includes knowledge graphs for data visualization, a data marketplace for buying and selling proprietary data, and a peer-to-peer environment for researchers to share insights. It also features a platform for knowledge-intensive crowdsourcing with a dynamic reward system. The native token, $PGPT, represents the value of datasets and is used for payments and contributions. The platform is built on a privacy-by-design methodology, utilizing Fully Homomorphic Encryption (FHE), Confidential Machine Learning (ConfML), and a Tendermint-based consensus to ensure data security and privacy. Use cases span across data analytics, research labs, GenAI companies, healthcare, and predictive modeling.
Skills
About the Role
You will be developing AI models that power a knowledge graph system designed to predict hidden links between different entities within scientific texts, revealing dependencies not explicitly mentioned in the text. You'll work on extracting knowledge graphs from both plain and encrypted scientific articles, analyzing raw data to define regularities based on user requests, and finding available knowledge graphs relevant to a user's search in the form of a word, phrase, or sentence. You'll also associate knowledge graph databases with corresponding articles in storage to serve as responses to user search requests. In return, you'll receive market-competitive remuneration, performance bonuses, and token vesting, plus opportunities to attend conferences and business events in global tech and finance hubs.
Requirements
- Strong proficiency in Python and R, Mistral, SpaCy and BERT
- Deep understanding of machine learning, including frameworks like TensorFlow, Keras, and PyTorch
- Expertise in natural language processing (NLP) and data analysis
- Experience with data visualization tools like Tableau and PowerBI
- Familiarity with big data technologies such as Hadoop and Spark
- Knowledge of cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)
- Experience with SQL and NoSQL databases
- Understanding of web technologies (HTML, CSS, JavaScript)
- Excellent project management and team leadership skills
- Background in scientific research data management (preferred)
- Experience with blockchain technology and cryptocurrencies (preferred)
- Experience with HELib, Microsoft SEAL, PALISADE, OpenFHE, TFHE, HEAAN, lattigo (preferred)
Responsibilities
- Extract knowledge graphs from scientific articles uploaded by scientific groups
- Extract knowledge graphs from preliminary encrypted scientific articles
- Analyze and define the regularities of raw data by user request
- Find the list of available knowledge graphs for a particular user request in the form of a word, phrase or sentence
- Associate the knowledge graph database with a list of corresponding articles in storage to provide responses for user search requests
Benefits
- Performance-dependent bonuses including commission from funding raised
- Token vesting
- Access to personal networks and prestigious memberships of the company, its advisors and the CEO
- Invitations to attend conferences or business events in global hotspots of tech and finance with expenses paid by the company