Portfolio — 2026
Engineering student — mechanical systems, applied AI, biomedical science.
Arts et Métiers ParisTech · BME Paris (PSL) · Neurotechnologies
About
I am a hybrid engineer — trained in mechanical and industrial systems at Arts et Métiers ParisTech (ENSAM), then applied data science and AI to real production environments, and now moving toward biomedical engineering and neurotechnology. Each domain informs the others: I approach AI with an engineer's rigour, and biomedical problems with industrial-scale thinking.
My internship at TECHWAVE proved that AI is most valuable when it survives contact with real constraints — local LLM inference for data confidentiality, hybrid rule-based/LLM pipelines to suppress hallucinations, tooling built for non-technical operators. I took a system from whiteboard to deployed production in four months.
In 2026 I join the BME Neurotechnologies Master (Université Paris Cité & PSL) — a research programme bridging biomedical engineering with computational neuroscience. My target: a lab at the intersection of AI and the nervous system — BCI, neural decoding, or neuromodulation — where the industrial and data background becomes an edge.
Arts et Métiers Gala — Viking Fountain, 2026
Background
Education
From competitive mathematics to industrial engineering, then biomedical AI — a deliberate trajectory, not a pivot.
BME Neurotechnologies
Master's — Neurotechnologies Track
Incoming · fully taught in English
- Neural signal acquisition: EEG, MEG, fMRI, intracortical recordings
- Neural decoding & signal processing
- Brain-Computer Interfaces (BCI) — design and evaluation
- Neuromodulation and neuroprosthetics
- AI applied to neuroscience data
- Clinical and regulatory context for biomedical devices
Arts et Métiers ParisTech — ENSAM
Diplôme d'Ingénieur — Mechanical & Manufacturing Engineering
- Mechanical design: gearbox sizing, shaft calculations, AGMA, SKF
- Manufacturing: machining (PFMC), isostatism, GD&T, FAO/CAM
- Industrial AI: Python pipelines, LLM inference, REST APIs
- Materials science: hot forming, metallurgy, quality control
- Student leadership: design and build of the Arts et Métiers Gala fountain
Lycée Marcelin Berthelot
Classes Préparatoires MPSI → PSI
- Rigorous mathematical foundations — analysis, algebra, geometry
- Classical mechanics, thermodynamics, physics
- Grandes Écoles competitive entrance track
Lycée Albert de Mun
Baccalauréat Scientifique — Highest Honours
- Mathematics, physics, engineering sciences (SI)
- Foundation for competitive preparatory classes
Selected Work
From industrial AI pipelines to mechanical design and autonomous systems — work that spans data, fabrication, and biomedical engineering.
Career
Experience
From early manufacturing internships to industrial AI deployment and junior enterprise leadership.
GE HealthCare / Imactis
Biomedical R&D — New Product Introduction Intern
- Contributing to a new CT-navigation product built on Imactis technology, supporting design-to-manufacturing transfer for image-guided interventional biopsy.
- Working across R&D, manufacturing and quality: process optimization, workstation improvement, documentation and traceability.
AMJE — Arts et Métiers Junior Enterprise
IT Officer — Chargé SI, IT/AI Pole
- Improve AMJE websites and internal IT tools; develop client-facing web platforms
- Automation and AI integration for internal operations
- Best Junior-Enterprise in France — CNJE Excellence Award 2024 · €300k+ annual revenue
TECHWAVE / OPEO
Industrial AI & Data Internship
- Intermediary between AI consultancy OPEO and TECHWAVE engineering teams
- Deployed 4 Python automation pipelines: BOM sourcing via Mouser API, regulatory requirement extraction, compliance matrix generation
- Hybrid rule-based + local LLM inference (Mistral via LM Studio) — 100% on-premise, zero data leaving the network
- Estimated impact: 102 days/year of manual work automated across procurement and compliance teams
MES / TECHWAVE Manufacturing
Engineering Internships
- 3D CAD modelling (SolidWorks) and rapid prototyping via 3D printing
- Improved SMT and screen-printing processes; supported Airbus A400M production line
Beyond the lab
Activities
Leadership, sport, and large-scale fabrication — the work that happens outside project pages.
Gala des Arts et Métiers — Viking Fountain
Team Lead — 10-person student build team
Led a 10-person student team to design and build a large-scale Viking-themed fountain for the Arts et Métiers Gala — an event gathering 4,000 guests in front of a historic building. Metal and wood structure, hydraulic circuit, runic decorations. Modular design enabled full assembly in under 2 hours on the night.
2026
Tennis — Arts et Métiers Association
President & Captain — Association Tennis ENSAM
President and captain of the Arts et Métiers tennis association. Managing operations, organising competitions and training sessions, representing the school in inter-school tournaments. Competing at a high level while building a team culture around discipline and performance.
2024–Present
Sailing — Competition & Offshore
Crew / Skipper
Competitive sailing since adolescence — regattas and offshore passages. Sailing demands the same instincts as engineering: reading dynamic systems, making decisions under uncertainty, and staying composed when things do not go as planned.
2019–Present
Expertise
Skills
A cross-disciplinary stack spanning industrial AI, mechanical engineering, and software development.
Programming & Data
AI & Machine Learning
Mechanical Engineering
Manufacturing & CAM
Tools & Workflow
Languages
Research
Interests
Seeking a 6-month research internship (Feb–Aug 2027) in a lab working on biomedical AI, BCI, or neurotechnology — US, UK, Switzerland, Singapore, or Canada.
Neural Decoding
Extracting intent, state, or cognitive content from neural recordings — EEG, intracortical, or LFP. Particularly interested in robust decoding under non-stationarity and limited training data.
Brain-Computer Interfaces
Closed-loop BCI systems that adapt to the user. The engineering challenge: real-time, low-latency decoding with interpretable outputs in clinical settings.
Biomedical AI
Machine learning on physiological data — where non-stationarity, limited labels, and interpretability requirements make standard pipelines insufficient.
Neuromodulation
Feedback-driven stimulation systems (TMS, tDCS, DBS). The intersection of control theory, hardware engineering, and neuroscience.
If you are a PI or lab manager with an opening — I would be glad to hear from you.
Get in touchGet in touch
Contact
Open to a 6-month research internship (available end Jan – early Feb 2027) in biomedical AI or neurotechnology — US, UK, Switzerland, Singapore, or Canada. I would be glad to hear from PIs or lab managers with relevant openings.
Pierre-Antoine Faribaud — Paris, France
Portfolio 2026