Machine Learning (ML) Engineer - Applied
Apply for this position →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.
Machine Learning (ML) Engineer - Applied
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.
Send your CV and a short introduction directly to the employer.