Artificial Intelligence Jobs

790 jobs for “Ai Developer”

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Isomorphic Labs logo

Isomorphic Labs · 201–500 people · Series A

Principal Software Engineer (Infrastructure)

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  • London
  • Hybrid · 3 days in office
  • Lead

Technically lead the Platform group, designing, operating and refining cloud infrastructure across research, development and production. Work spans GCP, Kubernetes, Docker, Terraform and Kapitan, plus CI/CD, observability and tooling, partnering with scientists, ML researchers and product teams. Reports to the Director of Engineering in a small, fast-moving team.

GCP · Kubernetes · Docker +7

4 days ago
Isomorphic Labs logo

Isomorphic Labs · 201–500 people · Series A

Medicinal Drug Design Lead

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  • London
  • Hybrid · 3 days in office
  • Lead

Lead medicinal chemistry strategy across drug discovery programmes, from hit identification through lead optimisation to candidate nomination, while working hands-on as an individual contributor. Partner closely with AI/ML platform teams to refine predictive models and manage CRO resources, mentoring junior colleagues without line-management duties.

AlphaFold

4 days ago

Darktrace · 2001–5000 people · Late stage

Machine Learning Researcher

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  • Cambridge
  • Hybrid · 2 days in office

Conducts independent and collaborative research into language models, neural networks, statistical methods and classical machine learning, prototyping new ideas and improving existing projects. Implements models into the wider software stack, including optimised solutions for edge devices with tight latency and memory constraints, working closely with software engineers and security analysts.

PyTorch · TensorFlow · scikit-learn +2

3 months ago

Darktrace · 2001–5000 people · Late stage

Senior Software Engineer (Python)

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  • Cambridge
  • Hybrid · 2 days in office
  • Senior

Owns the prototyping and development of new ideas to improve Darktrace's cybersecurity services, balancing creativity with time constraints to ship novel features. Works with a cross-functional team of engineers, designers and strategists on projects spanning rapid prototyping to structured platform development, with a focus on defending against unknown cyber-attacks.

Docker

2 months ago

PhysicsX

Machine Learning Engineer

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  • New York, United States
  • Hybrid
  • US$150,000 – US$190,000 pa
  • Mid-level

Delivery-focused role embedding physics-aware AI models into customer tools, working on-site with clients across aerospace, automotive and energy. Involves building reliable ML data pipelines, manipulating 3D point-cloud and mesh data, and translating R&D outputs into reusable libraries and products. Expects travel of 3-4 weeks per quarter to customer sites worldwide.

TensorFlow · MLflow · Spark +6

2 months ago

PhysicsX

Senior Machine Learning Engineer

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  • New York, United States
  • Hybrid
  • US$200,000 – US$250,000 pa
  • Senior

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization) into customer production environments, building scalable training and inference pipelines and APIs on cloud and on-prem. Leads scoping and architecture design, mentors engineers and data scientists, and travels to customer sites roughly 3-4 weeks per quarter to embed AI models on-site.

Python · PyTorch · Pandas +3

3 months ago

Luminance · 51–200 people · Series C

R&D Engineer

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  • Cambridge
  • Hybrid
  • Permanent

Designs and develops the core AI platform, building large-scale Python codebases and web-hosted services that power the company's software architecture. Works across the Python ecosystem, including Flask, Requests, NumPy and PyTorch, with scope to lead technical direction or teams. Open to graduates as well as experienced engineers.

Python · Flask · Requests +2

17 months ago

Luminance · 51–200 people · Series C

Delivery Engineer

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  • Cambridge
  • Hybrid
  • Mid-level
  • Permanent

Owns the software development lifecycle that produces packaged releases of an enterprise legal AI platform for distribution to clients. Day to day involves keeping the lifecycle efficient, unblocking the tech team, and analysing the SDLC for weak points to build human or automation solutions improving efficiency, reliability and visibility.

17 months ago

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