Acest post este localizat în Cluj-Napoca, Romania.
Oferim un post full-time.
Informații suplimentare
You might be our missing piece if you have:
- Deep expertise in Python and AI frameworks such as PyTorch (ideal), TensorFlow, Keras, or SciPy.
- Production-grade experience with FastAPI, Flask, or Django for serving AI models and building API-driven applications.
- Proven experience in architecting and scaling ML systems in production—everything from data pipelines and model deployment to monitoring and optimization.
- Experience with AI/ML architectures and AI-powered product architectures including: multi-agent architectures, multi-headed models, inference architectures.
- Experience with connecting data pipelines and serving inference processes.
- Strong hands-on knowledge of Docker and an understanding of containerized ML workflows (DevOps builds it, but you speak its language).
- Proficiency in SQLAlchemy, Alembic, and relational databases, along with a solid understanding of how to model, move, and optimize data for ML use cases.
- Expertise in data wrangling and preprocessing using tools like Pandas, NumPy, or SciPy.
- Experience integrating with and building on external AI APIs (e.g., OpenAI, Anthropic, Hugging Face, etc.).
- A solid understanding of software engineering principles, versioning (Git), and Python code style (PEP 8).
- A track record of leading AI/ML projects from ideation to deployment.
- Experience mentoring and guiding engineers, helping them grow technically and strategically.
We would be thrilled if you have:
- Exposure to research or academic papers, and a knack for translating theory into production-ready code.
- Comfort with cloud infrastructure (AWS, Azure, GCP, or DigitalOcean) and understanding of CI/CD best practices.
- Hands-on experience with LLMs, embeddings, semantic search, and tools like StableDiffusion or LLaMA.
- A collaborative mindset and the ability to bridge the gap between product, engineering, and research teams.
We will be working together on the following:
- Understanding clients' and their requirements and providing optimal solutions.
- Staying ahead of industry trends and implementing cutting-edge solutions.
- Technical leadership over major AI initiatives, from architecture design to final delivery.
- Mentoring and upskilling the AI team—pair programming, code reviews, and continuous learning are your bread and butter.
- Driving best practices around model development, reproducibility, monitoring, and scalability.
- Staying up to date with state-of-the-art advancements and continuously leveling up our AI capabilities.
