🌟 Evolwe https://evolwe.world - a deep tech company creating empathetic artificial intelligence technology and robots for human-like interactions and personalized experiences.

Evolwe AI has combined theory of mind, meta cognition, psychometrics, and NLP to create state-of-the-art AI architecture. Evolwe creates AI which is closest to humans in terms of providing empathy, reasoning and cognitive skills. We want AI to be empathetic, conscious and beneficial for society as a whole. We are creating a new generation of AI robots that can benefit companies and end users.

Why it’s great to work with us:

• An international product, complete geographical freedom, remote work.
• For us, money is a means, and the goal is to give a measurable benefit to the maximum number of people.
• The company is run by a founder with 14 experience in creating and successfully exiting international startups, with no bureaucracy.
• The company is essentially a combination of a startup (B2B and B2C products), and a R&D group (psychologists, linguists, mathematicians, and data scientists), we are interested in and we are making disruptive AI technologies.
• This is an extremely rare opportunity to come to the company at the perfect moment to get the most out of your efforts.

📌 Responsibilities:

1. Develop, refine, and optimize machine learning models, particularly focusing on user embeddings.
2. Conduct experiments to determine optimal values for autoencoder parameters: number of hidden linear layers and the dimension of the latent representation.
3. Collaborate with the team to create crawlers and parsers tailored for various social networks.
4. Analyze, preprocess, and utilize data collected from social networks to improve model performance.
5. Stay abreast of latest trends and developments in machine learning, particularly pertaining to user embeddings and social network data analysis.
6. Collaborate with interdisciplinary teams, including NLP specialists, to further the product’s capabilities.

📌 Qualifications:

1. Have 2+ year experience in ML engineering, defining research problems and identifying possible solutions.
2. Have recent experience in some combination of the following tools: NumPy, Pandas, Polars, SciPy, Scikit-learn, CatBoost, LightGBM, XGBoost, PostgreSQL, ClickHouse, NetworkX, Igraph.