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Machine Learning (ML) Engineer - Applied

ModelCat AI
Europe
Posted May 4, 2026
remoteunknown

Key details

Work type
remote

Job Description

ModelCat  |  Remote from Europe

About ModelCat

ModelCat is transforming how companies develop AI models for embedded, edge, and IoT devices. Our innovative platform uses AI to build AI — turning model architecture selection, training, optimization, and validation into a single powerful step.

ModelCat takes what was previously a 12–24 month process requiring highly skilled AI professionals and reduces it to a 24–48 hour AI-powered job that can be run by developers, data scientists, and product owners. Trusted by industry leaders like NXP and Silicon Labs, ModelCat is a venture-backed startup headquartered in Sunnyvale, California.

The Role

We're seeking a motivated ML Engineer to help advance our AutoML platform. You'll play a key role in expanding its capabilities, onboarding new ML use-cases across vision, time-series, and beyond, and improving the product as we scale. This role offers meaningful growth potential toward a technical leadership track.

What You'll Do

AutoML Platform Development

  • Contribute to the development and enhancement of our AutoML system for Edge AI, including pipelines that combine deep-learning and conventional algorithms for embedded devices Object tracking, multi-model pipelines, and emerging use-cases
  • Build and improve platform features across compute clusters and our web application
  • Define abstractions and contribute to the architecture of cloud, cluster, and embedded components

ML Use-Case Expansion

  • Integrate new ML use-cases across a broad range of data domains and maintain and improve existing ones, including: Time-series and audio, object re-identification, segmentation and keypoints Action recognition (video), radar and point cloud data, multi-modal (vision + audio + sensor) Small language models (NLP/SLM), classification, and object detection
  • Work with foundational computer vision and non-CV ML models — train, evaluate, modify, and combine them to unlock new functionality

Edge AI Optimization & Deployment

  • Optimize AI solutions for edge devices using TinyML frameworks, creating models that fit a range of chip sizes and memory constraints
  • Deploy ML and non-ML algorithms on embedded targets (MCU and application-class microprocessors)
  • Productize research-quality code into robust, production-ready systems

Collaboration & Craft

  • Partner on data strategies, preprocessing pipelines, and model training workflows
  • Stay current with Edge AI and AutoML advancements
  • Document your work and contribute to technical reports

Who You Are

Required

  • Master's degree in CS, EE, or a related field (PhD a plus)
  • 4+ years of relevant industry experience in ML (AutoML and Edge AI experience highly valued)
  • Strong Python skills with the ability to write production-quality code; C/C++ a plus
  • Solid command of ML frameworks: TensorFlow, PyTorch, ONNX
  • Proficient with the standard DS toolset: scikit-learn, OpenCV, pandas
  • Comfortable working in Linux-based development environments
  • Experience onboarding new ML use-cases and expanding into new data domains
  • Excellent problem-solving skills and strong written and verbal English communication

Preferred

  • Experience with cloud platforms (AWS) and web technologies (Node.js, REST APIs)
  • Familiarity with compute cluster tools such as Ray and Optuna
  • Knowledge of model compression techniques: pruning, quantization, transfer learning, knowledge distillation
  • Experience defining software architecture for ML systems
  • Familiarity with CI/CD practices
  • Understanding of embedded systems concepts
  • Experience with non-ML algorithms and signal processing

Mindset

  • Proactive, entrepreneurial approach — you thrive with ownership and ambiguity
  • Startup mentality: you move fast, learn faster, and care deeply about the outcome

Why Join ModelCat

  • Market Opportunity — Edge AI is exploding, and we're solving a critical pain point in a massive and growing market
  • Real Customer Impact — Our platform compresses 12–24 months of model development into 24–48 hours — validated by customers like NXP and Silicon Labs
  • Technical Depth — Work on hard, meaningful problems at the intersection of AutoML, TinyML, and embedded systems
  • Growth Trajectory — Join during a pivotal growth phase with significant room to grow into technical leadership
  • Competitive Compensation — Base salary, performance-based bonus, and meaningful equity stake

ModelCat is an equal opportunity employer committed to building a diverse and inclusive team.

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