NoFluffJobs Hybrydowo Senior

Senior Full Stack AI/ML Engineer

Mindbox Sp. z o.o.

⚲ Kraków

33 600 - 37 800 PLN (B2B)

Wymagania

  • AI
  • Python
  • Automated testing
  • PyTorch
  • TensorFlow
  • scikit-learn
  • Docker
  • Kubernetes
  • MLOps
  • MLflow
  • Kubeflow
  • RBAC

Opis stanowiska

O projekcie:
At Mindbox we connect top IT talents with technology projects for leading enterprises across Europe. 

 

We are looking for a highly autonomous AI/ML Engineer to design, build, deploy, and operate end-to-end AI/ML and Generative AI solutions at enterprise scale. This role is part of a major data transformation program enabling strategic initiatives for senior stakeholders by delivering business-critical insights, conversational AI systems, agent-based workflows, and advanced analytics solutions.

You will take full ownership of architecture, development, automated deployments, and post-production support of modern AI ecosystems, ensuring they are secure, scalable, compliant, and cost-optimized.

Sounds like your kind of challenge? 

What you get in return

- Flexible cooperation model – choose the form that suits you best
(B2B, employment contract, etc.)
- Hybrid work setup – 2 days from the office per week
- Collaborative team culture – work alongside experienced professionals eager to share knowledge 
- Continuous development – access to training platforms and growth opportunities 
- Comprehensive benefits – including Interpolska Health Care, Multisport card, Warta Insurance, and more 
- High quality equipment – laptop and essential software provided

Wymagania:
- 7+ years of software engineering experience, including 3+ years delivering production AI/ML pipelines or applications.
- Successfully delivered 2+ end-to-end AI solutions, including at least one enterprise conversational AI system deployed to production.
- Expert-level Python and strong understanding of software patterns, automated testing, and ML frameworks (PyTorch, TensorFlow, Scikit-learn).
- Hands-on experience with containerization and orchestration (Docker, Kubernetes), and automated deployments in cloud-native environments.
- Deep experience with multiple LLM families (e.g., GPT, Claude, Gemini, Llama, Mistral), prompt engineering, function-calling, workflow orchestration, and memory/state management.
- Proven experience delivering RAG systems (vector databases, hybrid search, embeddings, chunking, retrieval optimization).
- Working knowledge of agent-based frameworks: LangChain, LangGraph, Google ADK, plus familiarity with LlamaIndex, Semantic Kernel, AutoGen, CrewAI.
- MLOps/LLMOps tools (MLflow, Kubeflow), experiment tracking, compliance monitoring, model versioning, and automated evaluation frameworks (e.g., LangSmith, Ragas, DeepEval).
- Experience applying input/output guardrails, RBAC, PII masking, red-teaming, and secure AI controls.

Nice to have:

- Prior experience building enterprise AI platforms or reusable AI accelerators.
- Familiarity with financial services regulatory environments and compliance workflows.

Joining this project you’ll become part of Mindbox – a tech-driven company where consulting, engineering, and talent meet to build meaningful digital solutions. We’ll back you up every step of the way, accelerate your development, and ensure your skills make a difference.

Codzienne zadania:
- Collaborate with stakeholders to translate business requirements into innovative AI solutions, maintaining compliance with security and governance standards.
- Design and deliver production-grade AI/ML systems, including conversational AI, chatbots, agentic AI workflows, and RAG-powered applications.
- Build secure and scalable cloud-native architectures, leveraging platforms like AWS, GCP or Azure.
- Develop APIs, backend microservices, frontend components, and enterprise system integrations.
- Implement MLOps/LLMOps practices: monitoring, evaluation, model versioning, rollback automation, and guardrails.
- Optimize latency, reliability, and availability for real-time applications, ensuring <5s response time under expected workloads.
- Ensure compliance with AI governance, security measures, and data privacy regulations including input/output guardrails and adversarial robustness.

🔍 Dekoder Ogłoszenia

🔴
highly autonomous AI/ML Engineer
Oczekuje się, że będziesz pracować samodzielnie i podejmować decyzje bez ciągłego nadzoru.
🔴
take full ownership of architecture, development, automated deployments, and post-production support
Będziesz odpowiedzialny za cały cykl życia rozwiązań AI/ML, od projektu po utrzymanie.
🟡
enterprise scale
Rozwiązania, które będziesz tworzyć, będą musiały obsługiwać dużą liczbę użytkowników i danych.
🟡
major data transformation program
Projekt może być złożony i wiązać się z migracją lub reorganizacją istniejących systemów danych.
🔴
Flexible cooperation model – choose the form that suits you best (B2B, employment contract, etc.)
Choć model współpracy jest elastyczny, forma zatrudnienia (np. B2B) może wpływać na benefity i bezpieczeństwo socjalne.