Staff AI Engineer

Jobtailor; Paris; Sur place; EUR 90 000 - 130 000; Plein temps

Résumé du poste

Jobtailor is seeking a senior AI Engineer in Paris to design and deploy cutting-edge AI systems, including LLMs, vision-language models, and robust information retrieval pipelines. You will collaborate with software engineers, product managers, and business stakeholders to frame problems and deliver scalable, production-ready AI capabilities.

You will optimize metrics, run controlled experiments, and ensure reliability and observability across large-scale deployments while staying abreast of

Qualifications

• Experience taking models from prototype to production at scale.
• Hands-on development with LLM/VLM applications, including fine-tuning and benchmarking.
• Experience with information retrieval, hybrid search, and large-scale embeddings.
• Ability to design product-aligned metrics and run controlled experiments.
• Experience with production-grade monitoring, reliability, and observability.
• Strong Python coding skills and proficiency in SQL.
• Proficient written and verbal English communication.
• Nice to have: e-commerce or B2C marketplace experience.
• Nice to have: familiarity with MLOps practices and scalable processing frameworks (Dask, Ray, Spark).
• Nice to have: Bayesian and causal inference knowledge.

Responsabilités

• Design and implement AI solutions using LLMs, RAG, and agentic frameworks.
• Build and maintain information retrieval pipelines including hybrid search and vector databases.
• Develop and fine-tune LLM and vision-language models for product categorization and semantic search.
• Build agentic AI systems that interact with internal tools and data sources.
• Write production-ready code and deploy AI systems at scale.
• Define and track evaluation metrics, run A/B tests and benchmarks, and communicate results.
• Partner with engineers, product managers, and stakeholders to frame problems.
• Investigate production issues and ensure reliability and performance.
• Stay updated with Generative AI trends and scalable ML practices.

Connaissances

Machine Learning

Deep Learning

LLM Application Development

Information Retrieval

Python

Outils

W&B

MLFlow

Dask

Ray

Spark

Vector Databases

Description du poste

Responsibilities

• Design and implement AI solutions using LLMs, retrieval-augmented generation (RAG), and agentic frameworks


• Build and maintain information retrieval pipelines, including hybrid search, vector databases, and multi-stage re-ranking systems


• Develop and fine-tune LLM and vision-language models for product categorization, attribute extraction, and semantic search


• Build and orchestrate agentic AI systems interacting with internal tools and external data sources


• Write production-ready code and deploy AI systems at scale


• Define and track evaluation metrics, run A/B tests and benchmarks, and communicate results


• Partner with software engineers, product managers, and business stakeholders to frame problems


• Investigate and fix production issues and ensure reliability, observability, and performance


• Stay engaged with the latest AI trends, including Generative AI, agentic systems, and scalable ML

Requirements

• 5 to 10 years of experience in Machine Learning, Deep Learning, or AI Engineering, including taking models from prototype to production at scale


• Hands-on experience with LLM/VLM application development, including fine-tuning, prompt engineering, tool use, evaluation, and benchmarking


• Experience with information retrieval, hybrid search, large-scale embeddings, vector databases, and RAG architectures


• Experience building or orchestrating agentic AI systems


• Ability to design product-aligned metrics, run controlled experiments, and communicate results


• Experience with large-scale production applications, including monitoring, reliability, performance, and observability


• Strong coding skills in Python and proficiency in SQL


• Proficient oral and written communication skills in English


• User-focused mindset, strong analytical skills, and result-oriented approach


• Growth mindset


• Nice to have: e-commerce or B2C marketplace experience


• Nice to have: familiarity with W&B, MLFlow, Braintrust, and MLOps practices


• Nice to have: scalable processing frameworks such as Dask, Ray, or Spark


• Nice to have: Bayesian inference and causal inference familiarity


• Nice to have: recommendation systems and personalization knowledge

Core Competencies

Demonstrates expertise in designing and implementing AI solutions using LLMs and retrieval-augmented generation, with a strong focus on building reliable information retrieval pipelines and orchestrating agentic AI systems. Proficient in coding, evaluation metrics, and collaboration with cross-functional teams to drive product-aligned outcomes.

Highest-signal resume keywords

• Machine Learning


• Deep Learning


• LLM Application Development


• Information Retrieval


• Python

ATS Optimization Keywords

Hard Skills

• Machine Learning


• Deep Learning


• LLM Application Development


• Information Retrieval


• Hybrid Search


• Vector Databases


• RAG Architectures


• Production-Ready Code


• A/B Testing


• Evaluation Metrics

Soft Skills

• Proficient Communication Skills


• Analytical Skills


• User-Focused Mindset


• Result-Oriented Approach


• Growth Mindset

Industry Keywords

• E-Commerce


• B2C Marketplace


• Recommendation Systems


• Personalization


• Causal Inference

Tools & Technologies

• W&B


• MLFlow


• Dask


• Ray


• Spark