AI Engineer (Europe)
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AI Engineer (Europe)
Location
Budapest, , Hungary
Experience
Mid
Posted
Jul 18, 2026
Apply by
August 17, 2026
Applicants
0
Early applicantEasy applyContractHybrid
Job Description
## Company Description
We're Hiflylabs, a vibrant team of 250+ data and tech enthusiasts based in Budapest. From data engineering to data science, artificial intelligence and application development, we work on a wide range of projects around the world.
Over a Decade of Mastery:
For twelve years, Hiflyers have been reshaping industries through Data Warehousing, Business Intelligence, and Data Analytics. From consulting to operations, we offer tailored, hands-on solutions to complex business problems, helping our clients grow.
Our Commitment:
At Hiflylabs, we're not just about projects; we're about people. We believe that our people are our most valuable assets, and we are committed to nurturing their personal and professional development through our unique mentoring system.
Check out our [Website](https://hiflylabs.com/), [LinkedIn page](https://www.linkedin.com/company/hiflylabs/) and [YouTube](https://www.youtube.com/@hiflylabs) channel to get an insight into who we are and how we work!
## Job Description
What will you do?
- Own the architecture and delivery of production-grade LLM systems and classical ML solutions.
- Design, evaluate, and optimize RAG pipelines (retrieval strategy, chunking, indexing, monitoring).
- Build scalable, production-grade LLM services and agentic workflows, alongside traditional ML systems where appropriate.
- Define architecture trade-offs (LLM vs traditional ML, fine-tuning vs RAG, hosted vs self-managed models), with a strong focus on system-level optimization (latency, cost, scalability, reliability).
- Architect and optimize distributed GenAI and ML workloads on Databricks (Spark, MLflow), leveraging deep understanding of the platform ecosystem.
- Implement evaluation frameworks to measure quality, hallucination, and performance.
- Productionize systems with proper CI/CD, monitoring, rollback, and versioning.
- Independently design AI solutions tailored to client problems, translating business needs into scalable architectures.
- Lead technical decisions in client engagements and actively contribute to pre-sales architecture discussions.
- Mentor team members and define GenAI and ML best practices.
## Qualifications
What do you need to apply to this role?
- 5+ years of experience in Data Science or a related field.
- Proven experience delivering LLM-based systems to production (not only PoCs), as well as experience with classical ML projects.
- Strong hands-on experience with RAG, agents, and open-source LLMs.
- Deep understanding of system-level trade-offs (latency, cost, scaling, reliability), and experience optimizing production systems accordingly.
- Strong Python and SQL skills.
- Deep hands-on experience with Databricks and distributed computing (Spark), including performance optimization.
- Experience deploying scalable ML/LLM systems on AWS, Azure, or GCP.
- Ability to independently design end-to-end AI solutions in response to client problems.
- Client-facing experience and openness to participate in pre-sales processes.
- Clear, confident communication in English in technical discussions.
## Additional Information
“Data-driven digitalization, human-centered culture”
At Hiflylabs, we strive to create a work environment that is both challenging and supportive, allowing our employees to grow and excel with our company. We believe that our people are our most valuable assets, and we are committed to invest in their personal and professional development through our mentoring system.
- International projects, diverse challenges – Through Hiflylabs’ global nature you can work with clients and partners from all over the world. Are you ready for projects in New York, the Netherlands, Sweden, or Scotland?
- Advanced technologies - While immersing yourself in mind-blowing projects and tasks, you’ll discover cutting-edge tools & technologies.
- Empowerment - Trust is a cornerstone of our culture. We'll hold your hand if you need it, but give you space if you’d like to push your limits. Don't lose sight of the goal, the rest is up to you.
- Balanced life - We love what we do and aim to work together with others who do their work with love. At the same time, we highly value fresh minds, for which we think a healthy work/life balance is essential! Forget about pointless meetings and unnecessary administration.
- Mentoring from your first day – Continuous support is not just a set of fancy words we throw around here; your mentor follows you throughout your career path.
- Learning & Development opportunities - If you want to keep learning and improving, we are on to a great track! We look forward to helping you unlock your potential.
- Supportive corporate culture - In addition to our professional success, we are proud of the social cohesion that is based on comradery, mutual support, and respect and is constantly nurtured in the company.
Key Responsibilities
- Own the architecture and delivery of production-grade LLM systems and classical ML solutions.
- Design, evaluate, and optimize RAG pipelines including retrieval strategy, chunking, indexing, and monitoring.
- Build scalable, production-grade LLM services and agentic workflows alongside traditional ML systems.
- Define architecture trade-offs between LLM and traditional ML, fine-tuning vs RAG, and hosted vs self-managed models.
- Architect and optimize distributed GenAI and ML workloads on Databricks using Spark and MLflow.
- Implement evaluation frameworks to measure quality, hallucination, and performance.
- Productionize systems with proper CI/CD, monitoring, rollback, and versioning.
- Independently design AI solutions tailored to client problems and translate business needs into scalable architectures.
- Lead technical decisions in client engagements and contribute to pre-sales architecture discussions.
- Mentor team members and define GenAI and ML best practices.
Skills Required
PythonSQLDatabricksSparkMLflowRAGLLMsAWSAzureGCPCI/CDDistributed ComputingCommunicationClient-facing skillsMentoringProblem solvingTechnical leadership
Benefits
- Mentoring system
- Learning and development opportunities
- Work/life balance
- International projects
- Diverse challenges
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