1 day ago
Budapest, HungarySenior
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 LLM services, agentic workflows, and traditional ML systems where appropriate.
- Define architecture trade-offs involving LLMs, traditional ML, fine-tuning, RAG, hosted models, and self-managed models.
- Optimize distributed GenAI and ML workloads on Databricks, including Spark performance.
- Implement evaluation frameworks for quality, hallucination, and performance measurement.
- Productionize systems with monitoring, rollback, versioning, and delivery automation.
- Design end-to-end AI solutions for client problems and lead technical decisions during client engagements.
- Contribute to pre-sales architecture discussions, mentor team members, and define GenAI and ML best practices.
Requirements
- At least 5 years of experience in Data Science or a related field.
- Proven experience delivering LLM-based systems to production, beyond proof-of-concept work.
- Experience with classical ML projects and strong hands-on experience with RAG, agents, and open-source LLMs.
- Deep understanding of latency, cost, scaling, reliability, and other system-level trade-offs, with experience optimizing production systems.
- Strong Python and SQL skills.
- Deep hands-on experience with Databricks and distributed computing with Spark, including performance optimization.
- Experience deploying scalable ML and 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 willingness to participate in pre-sales processes.
- Clear and confident English communication during technical discussions.
Benefits
- Contractor role based in Europe.
- International projects with clients and partners across locations including New York, the Netherlands, Sweden, and Scotland.
- Mentoring from the first day and ongoing professional and personal development support.
- Learning and development opportunities involving advanced technologies and diverse projects.
- Supportive corporate culture with trust, collaboration, mutual support, and respect.
- Emphasis on work-life balance and reduced unnecessary meetings and administration.
Tech Stack
Categories
About Hiflylabs
Hiflylabs provides data engineering, analytics, AI/ML, and mobile application development for enterprises, delivering data warehouses, BI platforms, and cloud solutions. The privately held firm, founded in 2015 and headquartered in Budapest, operates as a consulting and implementation partner across AWS, Azure, Snowflake, and Databricks, where it holds partner status and MVP credentials. It serves customers in finance, telecom, energy, and other sectors in Europe and North America.