Machine Learning Operations Architect (with medical device experience)

We are scientists, doctors, techies and humanity lovers, with the mission of pioneering real time precision neurology to cure brain-related disorders. INBRAIN harnesses the extraordinary material properties of Graphene, the world’s thinnest and nobel-prize winning material, to build high resolution neural systems. Our mission is to decode and modulate neural networks to restore people's lives.

As a Machine Learning Operations Architect, you will architect and own the model lifecycle governance and deployment infrastructure. The role bridges MLOps engineering with medical-device design-control practice: it defines how models are versioned, validated, and promoted, and builds the change-control framework (aligned with a PCCP-style approach) that governs how adaptive, continuously-learning models can be safely updated post-deployment.

You will be at the forefront of bringing advanced healthcare solutions to market, making a tangible difference in people´s lives worldwide.

Main Responsibilities:

• Design and build the model versioning, lineage, and validation-evidence system that ties every trained model to its training data, the data source origin, risk management, and clinical evidence.
• Draft and maintain a Predetermined Change Control Plan (PCCP)-style framework defining permitted modification types, bounds, and automated re-validation protocols for adaptive models, in collaboration with clinical, regulatory, product and software stakeholders.
• Design and configure the CI/CD pipeline for training, validating, and promoting models, running on infrastructure provided by the Software team, with promotion gates across Development, Testing, Acceptance and Production (DTAP) tiers.
• Build drift and performance monitoring for models and define triggers for scheduled vs. drift-triggered retraining as part of post-market surveillance activity.
• Deployed and maintained processes and services versioning and tracing them against design-control processes.

Mandatory Qualifications and Soft skills:

• Bachelor's or Master's degree in Computer Science, Mathematics, Physics, Electrical Engineering or a related field.
• At least 4-5 years of Hands-on ML Ops engineering experience (preferably in medtech industry): model versioning/registries (MLFlow or equivalent), CI/CD for ML, containerized deployment (Kubernetes), and workflow orchestration (e.g. Argo or equivalent).
• Strong Architecture experience within industry setting (only academia or traineeship will not be considered).
• Proven experience shipping ML into a regulated or safety-critical environment (medtech - priority, automotive, aerospace), has designed systems to automatize design-control processes (e.g. IEC 62304, ISO 13485, DO-178C, ISO 26262) and has used them from the inside.
• Strong infrastructure-as-code skills and comfort directly supporting data scientists to productionize research code written in Python.
• Fluency in English required (English is company language).
• Direct experience with continuous/adaptive learning systems under a change-control or PCCP-like framework, delivering personalized evolving models in contrast to single model validation for universal use releases.
• Comfortable operating at the intersection of engineering and regulatory/clinical teams, translating design-control requirements into concrete technical implementation.
• Pragmatic about scope and sequencing — able to prioritize the governance/compliance work.
• Strong written documentation skills, given the role's heavy emphasis on producing auditable change-control and validation records.

Nice to have:

• Experience with FDA's Predetermined Change Control Plan (PCCP) guidance or equivalent adaptive-SaMD regulatory frameworks (e.g. through an imaging/diagnostic AI company that has filed one).
• Background in adaptive neurostimulation, closed-loop deep brain stimulation or closed-loop diabetes management with insulin pumps.
• Familiarity with clinical data standards (FHIR, SNOMED CT, NWB/BIDS) and ISO 14155/MDR/ICH E9 evidence frameworks.

We are looking for someone who Is ready to proactively bring new ideas to the team, push boundaries, and constantly look for innovation. At INBRAIN we believe in shared success and diverse ways of thinking, here you'll learn, grow, and advance in an innovative culture.

WHAT CAN WE OFFER TO YOU?

A collaborative environment where innovative ideas flourish and teamwork drives us forward. At INBRAIN, we believe the power of collective intelligence is unique. You will be part of a team that thrives on open communication, knowledge sharing and mutual respect.

Meaningful Work Impact: Our projects are not only exciting and challenging but also have a positive impact on the industry and society as a whole. You'll be part of a team that strives to create meaningful change.

Cutting-Edge Technology Exposure: Joining us means immersing yourself in the latest technologies and innovative solutions. You'll have access to state-of-the-art tools and resources, fostering continuous learning and keeping your skills relevant in a rapidly evolving industry.

• Competitive salary (according to your experience/skills)
• Internal flexible compensation scheme
• Private Health Insurance
• Training bonus for professional development and access to Udemy platform
• 23 vacation days per year
• Christmas week off
• Hybrid working modality

Applications must be submitted in English.

At INBRAIN, we're not just offering a job – we're inviting you to be part of a transformative journey, Are you ready to transform lives? Join us!

We believe that a diverse and well-balanced workforce drives innovation. At INBRAIN, we foster the inclusion of all people regardless of culture, age, gender, sexual orientation, identity and diverse abilities or any other status.