ML Engineer H/F

About the role

ML Engineer

Data & IA

Ippon Technologies represents a collective energy dedicated to technological excellence. Founded in 2002, we specialize in IT consulting, Data, Artificial Intelligence, Cloud infrastructure, and strategic IT architecture. We are a global team of over 600 passionate experts committed to helping clients achieve technical excellence through collaboration and innovation.

In 2017, our Lyon office was created, uniting 60 specialists who deliver high-technical-value solutions in software development, Data Science, and IT architecture. Our multidisciplinary approach, adaptability, and knowledge-sharing drive our commitment to client success and talent development.

Our mission is to guide clients through their digital transformation with technical excellence, collaboration, and a competitive mindset, enabling them to exceed expectations.

Join Our Data & IA Team

Our Data & IA division comprises 75 dedicated professionals focused on creating, developing, and deploying innovative Machine Learning and Generative AI solutions in the cloud. Following our expansion in AI activities since 2023, we are seeking an ML Engineer to contribute to technically and commercially impactful projects.

Your Role as ML Engineer

Designing and developing scalable AI and ML architectures for public cloud environments.

Integrating AI and ML models into existing production applications.

Establishing and optimizing MLOps pipelines to industrialize model workflows.

Implementing Generative AI solutions, including LLMs, RAG, and vector database systems.

Deploying customized or managed models according to client requirements.

Collaborating with Data Science, Data Engineering, DevOps, and business teams.

Monitoring technological trends and communicating ethical and legal AI considerations to stakeholders.

Promoting quality practices through testing, craftsmanship, and iterative improvements in cloud settings.

Our Technical Environment

Public Cloud: AWS, GCP, Azure.

AI and ML Platforms: SageMaker, Bedrock, Vertex AI.

MLOps: MLflow, Kubeflow.

Orchestration: Airflow, MWAA, Step Functions, Cloud Composer, Cloud Workflows.

CI/CD: GitLab, Terraform.

Containerization: Docker, Kubernetes.

Deployment: ECS, EKS, Lambda, Cloud Run, GKS, Cloud Functions.

Development: Python, FastAPI, Flask, LangChain, LlamaIndex.

Vector Databases: PostgreSQL (pgvector), OpenSearch, Vertex AI Vector Search.

Best Practices: Testing, craftsmanship, agility.

How We Support Your Career

Working within a team where you can propose your own ideas.

Receiving personalized guidance from a technical manager who understands your role.

Following a customized career path, including new responsibilities, mentorship roles, or technical management, with support for public speaking.

Accessing continuous training and certifications, particularly through our BlackBelt program covering AWS, GCP, Azure, mentoring, and coaching.

To explore our culture and technical expertise further, visit our technical blog at https://blog.ippon.fr/.

If this opportunity aligns with your ambitions, we encourage you to apply. We are eager to learn about your professional goals and present the Ippon adventure in greater detail.

About the Position

You are responsible for designing and deploying AI systems at scale; integrating models into live environments and coordinating MLOps workflows with Data Science teams. You will guide ethical AI implementation while challenging standards in collaboration with engineering and product partners.

Key Information

Location: Remote

Engagement: Full-time.

Compensation: 65,000 to 75,000 EUR per year.

Responsibilities

Architecting cloud-based AI structures to support elastic demand and rapid iteration cycles.

Integrating language and vision models into production software using established libraries and service patterns.

Orchestrating MLOps pipelines to automate validation, training, and delivery with monitoring instrumentation.

Creating AI features using retrieval methods and vector databases for context-aware enterprise queries.

Customizing large language models and managing endpoints to meet client specifications and performance objectives.

Coordinating with engineering, data, and business teams to refine requirements and resolve technical constraints.

Analyzing the AI landscape to identify new tools and communicating risk and compliance topics to stakeholders.

Championing quality practices through testing, craftsmanship, and iterative refinement in cloud environments.

Requirements

Demonstrated experience building machine learning applications in public cloud environments for at least three years.

Understanding of major model types and deployment patterns across cloud providers and container platforms.

Proficiency in writing Python for scalable services using frameworks for API and asynchronous request handling.

Experience managing infrastructure as code using declarative formats and version control workflows.

Preferred Experience

Hands-on experience with generative AI projects, vector databases, and retrieval augmented generation pipelines.