ML engineer confirmé

About the role

Ippon Technologies is seeking a senior ML Engineer to operate at the cutting edge of cloud-native artificial intelligence, where you will be responsible for defining scalable architectures and integrating advanced models into production environments. In this capacity, you will own the design of intelligent systems and ensure their seamless embedding within complex existing product landscapes. Your daily work will involve the rigorous evaluation of technical frameworks and the implementation of robust ethical oversight mechanisms. You will provide daily technical strategy guidance in the domains of cloud infrastructure, architectural patterns, and machine learning operations. This position represents a fully remote opportunity with flexible engagement terms, offering a competitive annual compensation package valued between 60,000 and 80,000 euros.

What you'll do

Analyze and design data orchestration workflows specifically tailored for both training and monitoring processes within cloud-native environments.

Construct and manage sophisticated vector stores along with retrieval mechanisms that form the backbone of generative applications.

Implement comprehensive MLOps automation by leveraging a diverse set of tools to guarantee dependable and continuous delivery cycles.

Develop and execute deployment strategies for managed services and bespoke models that effectively span GCP, AWS, and Azure ecosystems.

Collaborate intensively with data engineering and DevOps teams to ensure strict synchronization of pipelines with overarching product roadmaps.

Architect and build Retrieval-Augmented Generation (RAG) systems that successfully merge large language model reasoning capabilities with vector database precision.

Monitor the evolving AI landscape to evaluate emerging methods and subsequently disseminate relevant knowledge and best practices internally.

Translate complex technical concepts regarding legal and ethical implications into clear communication for clients and stakeholders.

Optimize and manage vector search technologies to ensure high performance and reliability in production settings.

Champion the adoption of infrastructure as code principles to maintain consistency and reliability across all deployments.

Lead proof-of-concept initiatives that validate new tools, frameworks, and methodologies for future scalability.

Mentor junior engineers by providing technical guidance and fostering a culture of continuous improvement and learning.

Ensure all solutions adhere to stringent security, compliance, and operational standards required by enterprise clients.

Drive the continuous refinement of existing pipelines to enhance efficiency, reduce latency, and optimize resource utilization.

Act as a technical liaison between engineering teams and business stakeholders to align technical capabilities with strategic goals.

Requirements

Candidates must bring a minimum of five years of hands-on experience specifically focused on building cloud AI or generative systems.

Mastery of Python, FastAPI, and LangChain is mandatory for the development of production-grade applications and services.

Demonstrate proficient configuration and management skills for PostgreSQL, pgvector, Elasticsearch, and a variety of vector search technologies.

Manage Docker, Kubernetes, and broader container orchestration platforms with expertise to optimize cloud workload performance.

Utilize pipeline automation tools such as MLflow and Kubeflow while applying rigorous testing methodologies to ensure quality.

Possess a deep understanding of major public cloud provider ecosystems, including their specific patterns, services, and operational nuances.

Exhibit experience with orchestration services such as Airflow, MWAA, Step Functions, Cloud Composer, and Cloud Workflows.

Showcase proficiency in Infrastructure as Code tools, particularly Terraform, to manage cloud resources effectively.

Apply strong problem-solving skills to debug complex issues in distributed systems and machine learning pipelines.

Communicate effectively in English, both in written and verbal formats, to collaborate with international teams and clients.

Nice to have

Familiarity with specific major cloud provider patterns across AWS, GCP, and Azure is advantageous for rapid onboarding.

Exposure to specific services like SageMaker, Bedrock, or Vertex AI provides additional context for solution design.

Understanding of orchestration services such as Airflow, MWAA, Step Functions, Cloud Composer, and Cloud Workflows is beneficial for streamlining workflows.

Practical notes

The engagement type is flexible, offering either contract or permanent arrangements.

The compensation package ranges between 60,000 and 80,000 euros annually.

This role operates in a fully remote context, allowing for geographic flexibility.