AI / ML Engineer (contractor, validation phase)

Humboldt-Universität zu Berlin

Alexandre Chicharo
Postdoc
Details
TRL 3 – Experimental proof of concept
Chemistry, Pharma & BioTech
Research & Development
Manufacturing, Production
Skills needed
Programming
Product Development
GreenTech / Climate
Pharma
Health
SaaS / Platform
AI / Data
DeepTech
MedTech
3-6 years
Entrepreneurial mindset
Deep expertise in the requested field
Mission-aligned
Willing to take risks & build from 0
Hands-on builder mentality
Long-term thinking
Collaborative but independent
Self-starter – doesn’t wait for instructions
Accountable – owns their work and doesn’t shift blame
Problem-solver – thrives on figuring things out
Strategic thinker – can connect dots and plan ahead
Application Form
Deadline
03/31/2026, 21:59
Working Conditions
Not set
Partly remote
About the job
nanoSpec is building nanostructured metamaterials plus an AI workflow to make chemical sensing faster and more reliable, starting with PFAS screening. This role is hands-on and outcome-driven. The goal is to move from “promising lab signals” to a repeatable validation package that can convince partners, customers, and funders. In the first weeks, you can expect to work with us on: • turning experimental data into a clean, versioned dataset (formats, metadata, QA) • defining the validation plan and metrics (LOD, reproducibility, calibration, robustness) • building baseline models / analysis pipeline (chemometrics + ML where it makes sense) We are early-stage and fast-moving. You’ll have real ownership, direct access to the founders, and a lot of autonomy, but also ambiguity. We want someone who can drive work independently and communicate clearly.
• A trial-first collaboration, start with a defined scope (e.g., 4–8 weeks) so both sides can test fit • Flexibility on structure: freelance/contract now, potential evolution to a larger role later if it works well • Real technical ownership, you help shape the validation strategy and the first product narrative • Access to lab partners and real experimental data, not toy problems • Potential equity discussion after the trial, based on contribution and commitment (not promised upfront) • Serious focus on building something fundable and sellable, not endless research Practical note: we’re pre-seed, so we optimize for impact per euro and we prioritize partners who want to build, not just advise.
About the startup project
nanoSpec Technologies is a Berlin-based deep-tech startup building nanostructured SERS substrates and an AI-driven analysis workflow to make chemical sensing faster, more reproducible, and easier to deploy outside the lab. Our first validation focus is PFAS screening (public health and regulatory relevance), starting with a substrate-first approach so labs can adopt it without changing their instrumentation. Over time, we plan to expand into a broader sensing platform across multiple chemical targets. We are an early-stage team with strong nanofabrication and sensing expertise, currently working with academic lab infrastructure for measurement and validation. We’re now looking for practical partners and team members to accelerate validation, data generation, and commercialization readiness (dataset quality, reproducibility, pilot use cases, and a clear path to market). https://www.nanospec.tech
Berlin
