Artificial Intelligence Jobs

• New York, United States
• Hybrid
• US$200,000 – US$280,000 pa
• Permanent

Owns the full enterprise sales cycle for a 1k–20k employee territory, from cold outreach and pipeline generation to closing and expanding multi-threaded relationships. Uses MEDDPICC to qualify opportunities and manages all activity in Salesforce, reporting to the Director of Enterprise Sales.

Salesforce

• Germany
• Hybrid · 2–3 days in office
• Mid-level
• Permanent

Founding pre-sales role building Synthesia's Solutions Engineering function for the DACH region, shaping the playbook, tooling and best practices as the team scales. Partners with Account Executives, Customer Success and Product Marketing on discovery, demos, POCs and technical solution design, covering API/SDK integrations, security and compliance topics such as SOC 2 and GDPR.

LMS · HCM

• Cambridge, United States
• Hybrid · 3 days in office
• Lead

Lead DMPK strategy across drug discovery projects, designing screening cascades and mechanistic experiments while integrating PK, PD and toxicology data for dose and safety predictions. Work within an AI-first preclinical team, shaping ADME predictive models and authoring regulatory documents to advance candidates toward first-in-human trials.

Python · R

• London
• Hybrid · 3 days in office
• Mid-level

Join the model performance and scaling team to implement and optimize LLM post-training methods on frontier models, collaborating with research teams to turn new methods into production-ready systems. The role focuses on distributed training and inference performance, low-precision methods, and frameworks like JAX or PyTorch, in a hybrid London setting.

JAX · PyTorch · NCCL +5

• Cambridge
• Hybrid · 2 days in office
• Director · manages people

Leads the strategy, roadmap and execution of Darktrace's interactive demo estate, managing a small team of technical content specialists. Partners with Product, Marketing, Enablement and Sales Engineering to evolve demos from on-rails walkthroughs into live sandbox environments, overseeing scenario, training and video content.

Reprise · Storylane · Navattic

• Cambridge

Join a global team continuously developing and improving threat detection capabilities across key product areas. You'll respond to customer incidents, analyse cyber threat intelligence, and expand detection schemes aligned to adversary techniques, collaborating with Development, Security Research and SOC teams.

Darktrace · GitLab · Python

• United Kingdom
• Remote
• Senior
• Permanent · Flexible

This role involves working closely with government clients and partners to design and deliver AI-driven solutions that address public sector challenges. The Solution Architect will develop technical strategies, lead proof-of-concept initiatives, and translate mission goals into scalable AI implementations using NVIDIA’s hardware and software platforms. A strong focus is placed on hands-on technical guidance, creating educational resources, and advocating for customer needs in product development.

• Cambridge
• Hybrid · 2–3 days in office
• Senior

Work on complex R&D projects within a Modelling Team that trains large self-supervised speech models and deploys them to production. Involves distributed training, transformer architectures, and inference optimisation, with mentoring and cross-department collaboration.

GQA · KV-Caching · Flash Attention +2

• London
• Hybrid · 2–3 days in office
• Senior

Join the Modelling Team to train large self-supervised and transformer-based speech models, deploying them into production with strong software engineering and model-serving practices. Work on complex R&D projects, optimise inference, and mentor engineers in a hybrid London setup.

GQA · KV-caching · Flash Attention +2

• Cambridge
• Hybrid
• Permanent

Join a small, dynamic R&D team prototyping and implementing new approaches to AI problems, evaluating output quality, efficiency and feasibility against other techniques in a data-driven way. Work spans data science on large datasets, modelling and evaluation, using Python ML frameworks such as PyTorch, TensorFlow and Scikit-Learn. Open to graduates as well as senior candidates with published work in NLP, Computer Vision or Deep Learning.

Python · PyTorch · TensorFlow +1

• London
• Mid-level
• Permanent

Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training workloads, identifying slow or faulty nodes and surfacing performance bottlenecks. Work deep in the stack across collective communication, parallelism, fault tolerance, and observability, collaborating with systems, infrastructure, and research teams to evolve the training platform.

• Sofia, Bulgaria
• Hybrid
• Senior

Senior backend role with a strong AI focus, designing and building cloud-native distributed services for the OMRS platform that runs thousands of autonomous robots across 120+ live sites. You'll use agentic AI tools daily to ship features faster, improve system stability, and shape how the whole team builds, including on-call duties.

Kubernetes · GCP · AWS +7

• United Kingdom
• Remote
• Lead · manages people
• Permanent

Hands-on technical leadership of the core platform services underpinning an AI product for regulated financial services, spanning client-data ingestion, CRM integrations and APIs, multi-tenancy, identity and data lifecycle. Leads roughly six to seven engineers while remaining close to production code, primarily Node.js on AWS with event-driven, distributed systems.

AWS · Node.js · Python +3

• New York, United States
• Hybrid
• US$150,000 – US$250,000 pa
• Senior

Builds and deploys customer-facing applications on top of physics AI models, working directly with clients, data scientists and ML engineers. Involves full-stack work: FastAPI REST APIs and Python microservices, plus cloud deployment with Helm, Kubernetes, Terraform and AWS/Azure. Expect on-site travel to customer sites for 3-4 weeks per quarter.

FastAPI · Helm · Kubernetes +3

• London
• Hybrid · 2–3 days in office
• Mid-level

Builds the simulation side of Large Physics Models, generating multi-fidelity CFD data to train large-scale ML models. Develops solvers and numerical methods in differentiable or GPU-native frameworks such as JAX or NVIDIA Warp, using commercial and open-source CFD tools for reference data. Works in a research team alongside ML researchers, shaping data generation strategy and fidelity tradeoffs.

JAX · NVIDIA Warp · OpenFOAM +2