[Hiring] AI Engineer @Hiflylabs

Role 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

• 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.

Benefits

• “Data-driven digitalization, human-centered culture” - A work environment that is both challenging and supportive, allowing employees to grow and excel.
• International projects, diverse challenges - Work with clients and partners from all over the world.
• Advanced technologies - Discover cutting-edge tools & technologies.
• Empowerment - A culture of trust that allows for personal growth.
• Balanced life - Emphasis on a healthy work/life balance.
• Mentoring from your first day - Continuous support throughout your career path.
• Learning & Development opportunities - Support for continuous learning and improvement.
• Supportive corporate culture - A focus on comradery, mutual support, and respect.