AI Machine Learning Engineer

Visium; Barcelona; Presencial; EUR 60.000 - 80.000; Jornada completa

Descripción de la vacante

Visium is seeking an AI Machine Learning Engineer in Barcelona to develop and deploy advanced AI initiatives. Candidates should have a strong background in Python and AI/ML architectures, combined with hands-on experience in cloud infrastructure and MLOps.

This role emphasizes collaboration in R&D-heavy spaces, aiming to deliver impactful AI solutions through disciplined software engineering. Full professional proficiency in English is mandatory, with French as a strong advantage.

Formación

• Senior proficiency in Python with software engineering best practices.
• Solid understanding of AI/ML architectures and data platforms.
• Deep knowledge of AI/ML algorithms and mathematical foundations.
• Proficiency in handling data structures and pipelines.

Responsabilidades

• Contribute to the design and development of scalable AI solutions.
• Deliver high-quality code for data, modeling, and deployment.
• Implement and maintain robust MLOps workflows.
• Work within an Agile framework to ensure predictable production value.
• Partner with stakeholders to translate challenges into requirements.

Conocimientos

Production‑Level Programming

System Design

Modeling Depth

Data Engineering

Azure

CI/CD

Containerization

Observability & Reliability

Agile Methodology

Technical Translation

Project Delivery

Educación

Master’s degree or higher in Computer Science, AI, Data Science, or a related field

Herramientas

Azure ML SDK/CLI

Azure Databricks

Docker

Descripción del empleo

Title

• AI Machine Learning Engineer
• Location: Barcelona

Role

As an AI/ML Engineer, you are a key technical contributor responsible for developing and deploying complex AI initiatives. You will focus on the end‑to‑end lifecycle of ML solutions—from technical design and coding to production deployment and continuous optimization. This is a high‑impact technical role. You will apply deep engineering rigor to build scalable, reliable systems that solve real‑world R&D challenges. You don't just build models; you ensure they are integrated into robust software architectures that meet the highest standards of performance and reliability.

Responsibilities

• 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.

Requirements

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 optimised.

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.