AI Engineer

Boulogne-Billancourt, Île-de-France, France

Acolad

Acolad is the global leader in technology-enabled localization services and content solutions.

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Acolad is the global leader in content and language solutions. Its mission is to support companies in every industry to scale across markets and enable growth through cutting-edge technology and localization expertise. Established in 1993, the group is present in 23 countries across Europe, North America, and Asia, with over 1.800 employees supported by a network of +20.000 linguists around the world.

At Acolad, every position is key to our global growth: we know that we will only succeed if our people succeed.

Joining Acolad means a unique opportunity for professional development through a collaborative global environment that promotes talent and creativity. We are continuously looking for new talent (like you!) to support our mission to drive growth and innovation across some of the world’s leading brands.

We are seeking a dynamic AI Engineer with proven expertise in deploying machine learning (ML) and deep learning (DL) models into production. You will play a key role in transforming AI models into production-ready applications, with a particular focus on LLM-native development, vector databases and building innovative AI-driven applications and services. In this role, you will collaborate with the data science team, driving experimentation, rapid iteration and the implementation of scalable AI solutions. A deep understanding of Python, cloud infrastructure (AWS, GCPorAzure) and experience with Large Language Models (LLMs) is essential.

Key Responsibilities

•Deploy and optimize ML/DL models: Ensure scalability, performance and reliability in production environments, moving from experimental to production-grade solutions.

•Develop LLM-native applications: Design, build and maintain AI applications utilizing large language models (LLMs), embracing an experimentation-driven process to unlock new capabilities.

•Leverage vector databases: Utilize vector databases to enhance retrieval performance and streamline AI workflows.

•Collaborate and iterate: Work closely with data scientists and product teams to integrate models and solutions into business operations, rapidly iterating through experimentation and proof-of-concepts (PoCs).

•Implement MLOps best practices: Ensure the continuous integration and delivery of AI models through MLOps pipelines, incorporating monitoring and feedback loops.

•Productization: Turn experimental models into production-ready applications by applying best practices in software engineering, cloud architecture and feedback mechanisms.

Requirements

•3+ years of experience deploying AI models: Proven experience in putting ML/DL models into production environments at scale.

•Expertise in building AI applications: Hands-on experience building AI-driven applications and services, with a focus on delivering practical solutions from experimental models.

•Experience with Large Language Models (LLMs): Strong understanding of LLMs, including their experimentation and productionization.

•Vector databases: Experience with vector databases for enhanced retrieval and AI performance.

•Proficiency in Python and cloud platforms: Deep expertise in Python and experience with cloud platforms such as AWS, GCP, or Azure.

•Research and experimentation mindset: Ability to design, experiment and iterate with LLMs and AI models, balancing lean experimentation and structured workflows.

•MLOps knowledge: Familiarity with MLOps pipelines, monitoring and optimization techniques for continuous delivery and feedback integration.

•Problem-solving and adaptability: Ability to navigate a fast-paced environment, embracing agility and continuous improvement in AI solution development.

Preferred Skills:

•Familiarity with prompt engineering techniques, such as few-shot learning and dynamic prompt optimization.

•Experience in creating PoCs and transitioning them into scalable, production-grade AI systems.

•Knowledge of caching strategies, cost optimization and debugging in LLM-based applications.

Acolad is committed to creating a diverse and equitable workforce. We believe that diversity, equity, and inclusion in all its forms - gender, age, disability, marital status, ethnic or social origin, religion, belief, or sexual orientation - enrich the workplace. It opens opportunities for individuals to express their talents, both individually and collectively, and strengthens our ability to adapt to a changing world. As an equal opportunity employer, we welcome and consider applications from all qualified candidates, regardless of their backgrounds.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Architecture AWS Azure Deep Learning Engineering GCP LLMs Machine Learning MLOps Pipelines Prompt engineering Python Research

Perks/benefits: Career development

Region: Europe
Country: France

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