AI Engineer (Computer Vision / ML Systems)

About the Opportunity

The Thinktank is partnering with one of our portfolio companies in the semiconductor and advanced imaging space. This company is building a digital twin layer for electron microscopy to improve training, safety, and productivity in high-precision lab environments.

Role Overview

This role is for an AI Engineer who will design, build, and deploy machine learning systems operating on real-world microscopy data. This is a highly applied, product-focused position—not a research role. The individual will own the full ML lifecycle, from raw data through production deployment.

What You’ll Do
Build and own end-to-end ML pipelines (data → training → deployment → monitoring)
Develop computer vision models for anomaly detection, segmentation, and feature extraction
Work with noisy, unstructured microscopy and sensor data
Optimize models for real-time or near real-time inference
Integrate models into production systems, APIs, and product workflows
Collaborate closely with product and engineering teams to translate models into usable features

Required Skills
Strong Python proficiency
Experience with PyTorch (or similar frameworks)
Solid understanding of computer vision (CNNs, transformers, feature extraction)
Experience building and deploying ML systems (not just training models)
Ability to work with imperfect, limited, or messy datasets
Strong problem-solving ability and ownership mindset

Nice to Have
Experience with microscopy, scientific imaging, or semiconductor data
Familiarity with semi-supervised or few-shot learning techniques
Experience with model optimization (e.g., ONNX, TensorRT)
Exposure to simulation environments or physics-informed ML

What We Look For
Ability to build and ship independently
Systems thinking beyond individual models
Comfort operating in fast-paced, ambiguous environments