AI Machine Learning Engineer

• Technical Implementation: Contribute to the design and development of scalable, maintainable AI solutions aligned with modern best practices.
• Hands-on Development: Deliver high-quality code for data, modelling, and deployment pipelines, leading the team through engineering rigor.
• MLOps Mastery: Implement and maintain robust MLOps workflows, focusing on automated CI/CD, containerization, and model observability.
• Agile Delivery: Work within an Agile framework to ensure research translates into predictable production value, meeting project milestones and deadlines.
• Business Advisory: Partner with technical and business stakeholders to translate business challenges into technical requirements and clear project updates.

Who you are

You are passionate about AI and driven to deliver real-world impact through data. You thrive in R&D-heavy environments involving sparse or high-dimensional data, excelling at the intersection of experimental AI research and disciplined software engineering. You are a clear communicator who can explain technical trade-offs to both engineering peers and business stakeholders.

Advanced AI/ML Engineering & Software Craftsmanship

• Production-Level Programming: Senior proficiency in Python, with a strong commitment to software engineering best practices (Design Patterns, Unit Testing, and Modular Code).
• System Design: Solid understanding of modern AI/ML architectures and data platforms to build robust, performant systems.
• Modeling Depth: Deep knowledge of AI/ML algorithms and the mathematical foundations required to tune models for high-precision R&D use cases.
• Data Engineering: Proficiency in handling data structures and pipelines to ensure model inputs are reliable and optimized.

Advanced MLOps & Cloud Infrastructure

• Azure: Hands-on experience with the Azure ML SDK/CLI or Azure Databricks, including managed online endpoints, compute clusters, and data assets.
• CI/CD: Experience building and maintaining deployment pipelines using Azure DevOps or automation in Gitlab.
• Containerization: Proficiency in Docker for packaging and scaling AI/ML workloads within cloud-native environments.
• Observability & Reliability: Ability to implement monitoring for system health (latency/CPU) and model performance (drift, accuracy, and data quality).

Professional Collaboration

• Agile Methodology: Experience working within an Agile/Scrum framework to deliver consistent project velocity.
• Technical Translation: Ability to communicate complex trade-offs clearly to non-technical stakeholders.
• Project Delivery: Proven track record of taking ML models from a research phase to a stable production environment.

Contextual Plus

• Academic Background: Master's degree or higher in Computer Science, AI, Data Science, or a related field.
• Domain Expertise (Preferred): Exposure to formulation, chemistry or the Fragrance & Flavour industry.
• Languages: Full professional proficiency in English; French is strongly preferred.

What we offer

• A competitive compensation package
• A yearly education budget to steep your learning curve
• A yearly sport budget because a fit body leads to a fit mind
• A flexible working culture because your work-life balance matters to us
• A position that enables you to have an impact on 1'000s of people, and the whole company's growth.
• An international, knowledgeable, and passionate team with a strong collaborative mindset