обновлено 13 часов назад
Lead AI Engineer
110 000 - 130 000€
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Lead AI Engineer (LLM/RAG): Building and deploying scalable enterprise AI systems, including LLMs, agentic workflows, RAG pipelines, and production ML infrastructure with an accent on model fine-tuning, evaluation, monitoring, and inference optimization. Focus on designing reliable high-throughput systems, solving latency and drift challenges, and establishing AI architecture standards across the platform.
Location: Hybrid in Lisbon or Madrid
Salary: €110,000–€130,000 per year plus performance bonuses
Company
is a high-paced startup building enterprise-grade AI capabilities and client-ready AI-driven features.
What you will do
- Drive the technical direction of the AI stack and act as the Chief of AI’s technical right hand.
- Design, develop, fine-tune, and deploy ML models and LLMs in production at scale.
- Build scalable data ingestion, transformation, feature engineering, and fine-tuning pipelines.
- Implement RAG workflows, vector search, knowledge grounding, and enterprise-grade agentic workflows.
- Develop automated evaluation, monitoring, and experimentation frameworks covering latency, accuracy, drift, and retraining.
- Optimize inference speed, memory usage, cost, reliability, and throughput while mentoring engineers and collaborating with product and delivery teams.
Requirements
- 5+ years of experience in data engineering, ML engineering, applied AI, or comparable deep technical roles.
- Production experience deploying ML models and LLMs at scale, including inference optimization.
- Hands-on experience with LangGraph, LlamaIndex, or similar agent orchestration tools.
- Experience training deep-learning models and fine-tuning LLMs with Python and a major deep-learning library such as PyTorch, TensorFlow, or JAX.
- Experience building production-grade batch or streaming data pipelines with tools such as Airflow, Spark, or Dagster.
- Knowledge of ML theory, cloud platforms, containerized deployments, MLOps, RAG, vector databases, embeddings, monitoring, reproducibility, and CI/CD for ML.
Nice to have
- Experience in regulated or enterprise environments such as banking or insurance.
- Technical leadership, architecture ownership, or experience acting as a technical right hand to a CTO or Chief of AI.
Culture & Benefits
- Flexible work setup with travel when needed.
- Performance bonuses and access to an equity or share plan as it rolls out.
- Health and wellness allowances plus private health insurance.
- 25 days of paid time off, excluding local public holidays.
- Builder-oriented environment focused on impact, quality, ownership, collaboration, and growth.
Hiring process
- Introductory 30-minute call followed by a culture and values interview.
- Live coding challenge and delivery and collaboration interview.
- Most candidates complete the process within 2–3 weeks, followed by an offer conversation.
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