AI Software Developer

5 dni temu


Warszawa, Polska TeaCode S.C. Pełny etat

We are a software house based in Warsaw with over 50 people on board, seeking an experienced AI Software Developer to join our team. In this role, you will be responsible for designing, developing, and implementing advanced machine learning algorithms and systems.

About the Role:
  • Key Responsibilities:
  • Design, develop, and implement advanced machine learning algorithms, models, and pipelines using Transformers, PyTorch, Numpy, and Pandas.
  • Partner with our customers to understand their challenges and deliver technical solutions that meet their specific needs while navigating the complexities of productionizing AI.
  • Write production quality code using standard software engineering best practices (git, testing, etc.).
  • Stay up-to-date with the latest advancements in Machine Learning and AI.
  • Collaborate with customers to design robust, scalable systems that leverage AI, from proof of concept through full production deployment.
Requirements:
  • 3-5 years of relevant experience in similar roles, ideally working on large-scale machine learning projects.
  • Bachelor's degree in Computer Science, Machine Learning, or a related field; or equivalent industry experience.
  • Expertise with Transformers, PyTorch, Numpy, and Pandas, alongside strong software development best practice.
  • Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes).
  • Experience with new AI tools (e.g. Llamaindex, Copilot/Cursor, vector databases, Langchain) and techniques.
  • Demonstrated experience building AI apps in production.
  • A strong drive to stay ahead of the curve with AI research and apply those insights to help customers build real-world applications.
  • Excellent command of English (written and spoken), min. B2+ level.
  • Proficient or native Polish speaker.
Nice to Have:
  • Experience deploying AI systems in production environments, including scalability and optimization.
  • Understanding of deep learning architectures such as Transformers, Convolutional Neural Networks.
  • Familiarity with adjacent technologies such as edge AI, reinforcement learning, computer vision, or natural language processing (NLP) at scale.


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