Filuta AI: Democratizing Intelligent Automation

Filuta AI democratizes intelligent automation as a platform by enabling efficient creation of composite AI solutions through a combination of self-supervised learning and automatic symbolic domain synthesis techniques. We are highly innovative, ambitious, well-funded, and rapidly growing with customers in the EU and US, biting into a booming $600B/y intelligent automation market (>$1T in 2026) and providing tangible ethical value across a multitude of industries.

We are looking for a Data Engineer and Machine Learning Researcher in one person to join our team.

Role Description:

In this position, you will build customer prototypes as well as our composite-AI platform. Most of the projects assigned to you are going to require an end-to-end approach; from customer communication, data understanding, and data preparation to building functioning and scalable code and AI/ML models and algorithms. This broad range of responsibilities falls into the rank of data science, ML, and research.

You will problem-solve. Every new prototype we build is an unexplored territory and a hard nut to crack. Do whatever is necessary to find the best solution for the customer. Do not expect to have data at the top-notch quality available, be ready to question everything and build your own way towards the end goal. Our prototypes are being implemented in a broader span of industries; logistics (food delivery optimization), gaming (Gaming QA automation), manufacturing (planning optimization for construction sites).

Typical Tasks in the Role:

  • Analyze both structured and unstructured data.
  • Create analytical solutions, from data gathering to display; construct data engineering pipelines.
  • Deploy, test, validate, and maintain AI / ML models and solutions according to business goals and customer needs.
  • Improve and broaden current ML frameworks and libraries.

Upon productionalizing, after we as a company successfully deliver several prototypes and build our composite-AI platform, your tasks would gradually shift in DWH, data architecture, and MLOps areas in order to better streamline the increasing number and complexity of our solutions and products.

Required Qualifications:

  • Proficiency in Python (other languages are an advantage).
  • Experience in MLOps (building and deploying machine learning models in production).
  • Practical understanding of ML frameworks, libraries, and concepts.
  • Experience working with data ingestion tools.
  • Strong proficiency in data pipelines and workflow management tools (e.g., Airflow, Luigi, Kedro, Flyte, Dagster).
  • Master's or PhD degree in math, computer science, statistics, or a related field.

Nice to Have:

  • Working knowledge of Cloud-based solutions (e.g., AWS, Azure, GCP).
  • Working knowledge of Google OR-tools, IBM docplex, Gurobi.
  • Experience with distributed computing frameworks, such as Spark, Ray, Celery.
  • Experience working with cloud Data Warehouse solutions (e.g., Snowflake, Redshift, BigQuery, Azure, etc.).

Job Features:

  • Joining early a well-funded deep-tech disruptive AI startup.
  • Opportunity to build and contribute to the key architecture decisions across our projects and platform.
  • Opportunity to ramp-up on bleeding-edge artificial intelligence technologies, cooperating with the top AI scientists in the field.
  • Working with a highly motivated team of outstanding people.
  • Significant equity stake.
  • Office in Prague, Czech Republic. Future relocation to the USA is possible.

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We were supported by the system project Technological Incubation



The AIPlan4EU project is funded by the European Commission – H2020 research and innovation programme under grant agreement No 101016442

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