Applied AI Engineer
New
T
TalenticaAI, Software Engineering
The successful candidate will work from Poland, No fixed company-wide working schedule, but team members are expected to maintain sufficient working-hours overlap with their immediate colleagues to collaborate effectively.Full-TimeMiddle
SalaryThe compensation package consists of a base salary and equity. Compensation is determined individually based on professional experience and technical capability, scope of responsibility, location and relevant market benchmarks, and expected impact on the product and organization.
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Job Details
- Required Skills
- PythonMachine LearningPyTorch
Requirements
- Strong foundations in Machine Learning and modern neural network architectures.
- Hands-on experience training, fine-tuning, or deploying Machine Learning models.
- Ability to write clean, maintainable, and production-quality code.
- Confidence working across multiple abstraction layers—from models and infrastructure to product behavior.
- Strong problem-solving skills in ambiguous and rapidly changing environments.
- A delivery-oriented mindset focused on shipping, measuring, iterating, and continuously improving production systems.
- Proficiency in Python.
- Experience with PyTorch or JAX.
- Experience with LLMs, including OpenAI-compatible APIs, LLaMA, and Qwen.
- Experience with model inference and serving (e.g., vLLM).
- Familiarity with vector databases.
Responsibilities
- Build and ship AI features end-to-end, from the model and supporting systems to the user experience.
- Design and continuously improve prompts, tools, memory systems, and agent workflows.
- Transform raw model outputs into structured, reliable, and predictable product behavior.
- Diagnose and resolve issues across models, orchestration, infrastructure, and user experience.
- Optimize systems for latency, operational cost, and production reliability.
- Develop lightweight evaluation frameworks to measure real-world model and product performance.
- Work closely with product and engineering teams to transform ambiguous problems into production-ready systems.
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