Machine Learning Engineer

Intellectual Capital Resources; Oxford; Hybrid; GBP 59,000 - 99,000; Full time

Benefits offered by this job

Bonus

Equity

Remote/hybrid setup

Learning & development

Job summary

Intellectual Capital Resources is hiring a Machine Learning Engineer to build and deploy production ML systems for complex IC verification. The role emphasizes end-to-end development from data ingestion to model deployment, with strong Python and PyTorch/JAX skills and experience in data pipelines.

You will work in a deep-tech startup setting with a flexible remote/hybrid setup centered around London, Cambridge, and Oxford, collaborating with researchers and customers on real workflows.

Qualifications

• First degree in a relevant STEM subject.
• 3+ years of industry experience building production ML systems.
• Expertise in Python and PyTorch/JAX for training, inference, and model export.
• Experience building data pipelines for complex scientific or engineering datasets.
• Solid software engineering fundamentals, including testing, CI/CD, and clean APIs.
• Experience owning end-to-end ML systems from data ingestion to model deployment.
• Clear communication skills, including writing specs, documenting APIs, and presenting to customers.
• Familiarity with circuit simulation or EDA tools is a plus.
• C++/CUDA experience for performance-critical components is a plus.
• Experience in a startup or fast-moving team environment.

Responsibilities

• Build next-generation machine learning tools that transform how complex integrated circuits are verified.
• Accelerate simulation coverage and reduce tapeout risk for chip design teams.
• Own end-to-end ML systems from data ingestion through model deployment.
• Build and maintain data pipelines for scientific and engineering datasets.
• Develop training, inference, and model export workflows using Python and PyTorch/JAX.
• Write specifications, document APIs, and present technical work to customers.
• Collaborate closely with researchers and work with real customer workflows.
• Contribute to production chip-design tools used by semiconductor customers.

Skills

Python

PyTorch

JAX

Data pipelines

CI/CD

Testing & APIs

End-to-end ML systems

Communication skills

Startup environment

C++/CUDA (plus)

Education

Bachelor's degree in STEM

Tools

CUDA

CI/CD tooling

APIs

Job description

Salary: £59,000 - 99,000 per year

Requirements:

• First degree in a relevant STEM subject
• 3+ years of industry experience building production ML systems
• Expertise in Python and PyTorch/JAX for training, inference, and model export
• Experience building data pipelines for complex scientific or engineering datasets
• Solid software engineering fundamentals, including testing, CI/CD, and clean APIs
• Experience owning end-to-end ML systems from data ingestion to model deployment
• Clear communication skills, including writing specs, documenting APIs, and presenting to customers
• Familiarity with circuit simulation or EDA tools is a plus
• C++/CUDA experience for performance-critical components is a plus
• Experience in a startup or fast-moving team environment

Responsibilities:

• Build next-generation machine learning tools that transform how complex integrated circuits are verified
• Accelerate simulation coverage and reduce tapeout risk for chip design teams
• Own end-to-end ML systems from data ingestion through model deployment
• Build and maintain data pipelines for scientific and engineering datasets
• Develop training, inference, and model export workflows using Python and PyTorch/JAX
• Write specifications, document APIs, and present technical work to customers
• Collaborate closely with researchers and work with real customer workflows
• Contribute to production chip-design tools used by semiconductor customers

Technologies:

• CI/CD
• CUDA
• Support
• Machine Learning
• PyTorch
• Python

More:

We are a deep-tech startup specialising in machine learning, building next-generation tools to transform how complex integrated circuits are verified. Our technology accelerates simulation coverage and reduces tapeout risk, giving chip design teams a major step-change in capability. This is a high-impact opportunity for a Machine Learning Engineer to make a difference in silicon. We offer a competitive salary, bonus, and meaningful equity, along with a flexible remote/hybrid setup based around London, Cambridge, and Oxford. We also support learning and development, and you will work closely with researchers while gaining exposure to real customer workflows. Your work will ship to real semiconductor customers and run inside production chip-design tools.