Machine Learning Engineer with GenAI Asset Creation Platform @
6 days ago
- Minimum 3 years of experience in Machine Learning, with strong hands-on coding skills (Python).
- 1–2 years of experience with image generation models (e.g. Stable Diffusion, DALL·E, or custom diffusion models).
- Practical experience with deep learning frameworks (PyTorch preferred).
- Familiarity with Transformers, CLIP, and latent diffusion architectures.
- Ability to fine-tune and deploy models for production use.
- Experience working with cloud platforms (AWS or GCP).
- aComfortable working with Docker, APIs, and MLOps best practices.
- Strong product mindset – experience building tools used by non-technical end users is a plus.
Job Description: We're looking for a Mid/Senior Machine Learning Engineer with deep expertise in Generative AI to support our client in building AI-powered tools for large-scale ad asset generation.
Project context: Client is developing a GenAI platform used by enterprise marketing teams to generate complete ads (not just text or images). The product connects directly to media accounts, uses brand assets, and applies brand guidelines automatically. Backed by a major international group with strong traction in Fortune 500 clients.
Seniority: Mid with 3+ years of relevant experience
Requirements:
- Minimum 3 years of experience in Machine Learning, with strong hands-on coding skills (Python).
- 1–2 years of experience with image generation models (e.g. Stable Diffusion, DALL·E, or custom diffusion models).
- Practical experience with deep learning frameworks (PyTorch preferred).
- Familiarity with Transformers, CLIP, and latent diffusion architectures.
- Ability to fine-tune and deploy models for production use.
- Experience working with cloud platforms (AWS or GCP).
- aComfortable working with Docker, APIs, and MLOps best practices.
- Strong product mindset – experience building tools used by non-technical end users is a plus.
Remote vs Onsite: Remote or hybrid from our office in Kraków
Salary: 80 - 100 PLN/hour B2B
Wysyłając zgłoszenie rekrutacyjne, zgadzasz się na przetwarzanie Twoich danych osobowych przez NUMLABS sp. z o.o. z siedzibą w: Emaus 5, 30-201 Kraków (Pracodawca), jako administratora danych osobowych w celu przeprowadzenia rekrutacji na stanowisko wskazane w ogłoszeniu
,[] Requirements: Python, AI, Machine learning, PyTorch, AWS, Docker, APIS, MLOps Additionally: Sport subscription, Small teams, International projects, Free coffee, Shower, No dress code.-
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