Data Scientist/ Machine Learning Engineer

You will contribute to building a next-generation platform that leverages cutting-edge advancements in AI and machine learning. 

The role focuses on agentic AI, generative AI, and deploying modern LLM-powered solutions across real-world use cases.

What is the project idea?

Our client is from the USA and is the founder of one of the largest AI/ML communities worldwide. 

This project aims to build a series of models and decision intelligence signals to help our clients with decision-making.

What is so great about this project?

It’s a project for someone looking for a new challenge and a great learning experience.

Our primary focus is Machine Learning, Data Science, and AI areas, and we have a lot of expertise in these areas.

Who are the people I am going to work with?

You will work with a Team Lead and a PM on our side. Also, there is a Senior Data Scientist on the client’s side involved in the project development, which makes up a highly skilled and fun team to work with.

How many stages of the interview are there?

– Interview with the Recruiter – up to 30 min.;

– Technical interview – up to 1 hour;

– Interview with the client.

Requirements

Hard skills

- 3+ years in a data science or ML engineering role with production-level deployments;

- Strong Python skills, including libraries such as pandas, NumPy, and scikit-learn;- Solid understanding of classical ML models (e.g., Random Forests, XGBoost, regression/classification);

- Experience designing and maintaining end-to-end data pipelines using Apache Airflow and SQL (PostgreSQL, MySQL);

- Proficiency in data ingestion, including web scraping (BeautifulSoup, Scrapy) and API integration;

- Hands-on experience with RAG pipelines and vector databases (e.g., Weaviate);

- Background in NLP tasks (named entity recognition, sentiment analysis) using spaCy, NLTK;

- Familiarity with model validation techniques (cross-validation, A/B testing);

- Experience building and maintaining data lakes and warehouses;- Competency in data visualization (matplotlib, Plotly, or similar);

- At least a B2 level of English.

Nice to Have:

- Experience with LLM fine-tuning or prompt engineering;

- Familiarity with LangChain, LlamaIndex, or similar frameworks for agentic AI workflows;

- Understanding of LLM evaluation and orchestration using AI agents.

Soft skills

- Excellent problem-solving ability and experimental mindset;

- Strong communication and documentation skills;

- Comfortable in a flexible, fast-paced environment with evolving priorities.

Responsibilities

- Design and implement ML systems, including classification, regression, time-series models, and LLM-based applications (e.g., AI agents, RAG, summarization, QA);

- Build and maintain ETL pipelines with Python and Apache Airflow;

- Conduct data analysis, cleaning, and validation to extract insights;

- Work with vector databases (e.g., Weaviate) to support RAG pipelines;

- Prototype and deploy AI-powered tools, including conversational and summarization interfaces;

- Apply NLP techniques such as NER and sentiment analysis using spaCy and NLTK;

- Create visualizations and dashboards with matplotlib, Plotly, or similar tools.