AI Engineer

SPRIBE is an innovative B2B iGaming software developer reshaping the industry with cutting-edge technology and a forward-thinking approach to game design. The company pioneered the crash-game format with its flagship title Aviator, setting a new standard in player engagement and paving the way for a wave of non-traditional content. With over 62+ million monthly active players, SPRIBE is now the most influential company in the market. Alongside Aviator, SPRIBE builds forward-thinking solutions like the Broadway Platform, enabling operators to launch and scale with exceptional speed and efficiencyStrategic global partnerships with iconic brands such as UFC, WWE, and AC Milan, along with a roster of 12 global brand ambassadors, reflect the company’s bold vision for international growth and its commitment to expanding its presence across worldwide markets.


We are looking for a Middle ML/AI Engineer to drive the intelligence behind automated Chat Moderation systems.
You will build hybrid AI solutions that effectively balance processing latency with high classification accuracy.
This role is critical for maintaining platform integrity and user safety. The focus is on developing custom Neural Network models and implementing hybrid logic to ensure that complex content violations are detected efficiently while maintaining real-time performance for standard traffic.

Requirements
Required Qualifications & Skills
- ML/NLP Experience: 2+ years of hands-on experience in NLP.
- Embeddings: Practical experience with Embedding Models and RAG.
- Transformer Proficiency: Comfort with the HuggingFace ecosystem—loading, fine-tuning, and evaluating transformer models.
- Hybrid AI Understanding: Experience or strong conceptual understanding of combining deterministic ML with Generative AI (LLMs) in a single pipeline.
- Coding Standards: Strong Python skills with an ability to write clean, maintainable, and typed code.
- Data-Centric Approach: Experience dealing with real-world, messy data—cleaning, labeling strategies, and handling class imbalance

Responsibilities
- Hybrid System Evolution: Participate in the design of hybrid flows that combine classical models and LLMs. Help lay the groundwork for dynamic routing capabilities between model types.
- Model Training & Fine-Tuning: Train and fine-tune ML and LLM models for specific content moderation tasks.
- LLM Integration: Implement workflows to handle "corner cases"—complex messages that require reasoning capabilities beyond standard classifiers.
- Data Strategy: Manage the data lifecycle, including data augmentation, labeling strategies, dataset balancing, and integrating feedback into training sets.
- Performance Optimization: Ensure the moderation pipeline supports both real-time (low latency) and batch processing requirements.
Technologies
- Programming: Python
- ML Frameworks: PyTorch, HuggingFace, Transformers, sentence-transformers, scikit-learn.
- GenAI & Orchestration: LiteLLM, LangChain, LangGraph.
- Cloud: AWS (SageMaker, Bedrock)

Work conditions
Why join SPRIBE
Flexible work modelWork from our modern offices in Warsaw or Tbilisi, or remotely if you're based in another city
— we support your comfort and productivity wherever you are.
Top-tier equipment
We provide and deliver all necessary corporate hardware so you can start strong from day one.
Generous paid time off
Enjoy 26 business days of paid vacation annually, plus paid sick leave — because we value your well-being and work-life balance.
Health & wellness support
Our benefits catalog lets you choose what matters most:
-Gym membership compensation
-English language courses
-Medical insurance
Celebrating your moments
We recognize and celebrate your birthdays and work anniversaries with thoughtful gifts — because your milestones matter.
Global team events
Twice a year we host unforgettable corporate events in some of the world’s most exciting cities — a unique blend of team spirit and adventure.