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DocuWare stands for globally distributed, international teams and an open corporate culture that invites you to help shape it. Mobile Work and flexible working hours are part of our everyday life. Would you like to be…

Helsing is a defence AI company. Our mission is to protect our democracies. We aim to achieve technological leadership, so that open societies can continue to make sovereign decisions and control their ethical standards.

"Founded in 1927, the Volvo Group is committed to driving prosperity and shaping the future landscape through sustainable transport, mobility, and infrastructure solutions. By offering trucks, buses, construction…

At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we’re building the delivery of (almost) everything and…

The AI platform is responsible for all AI infrastructure across Datadog. Our mission is to

• Previous experience (1+ years) leading software engineering teams, as a tech lead or people manager
• Strong technician with a mix of backend, data engineer and infrastructure experience who is interested in remaining a hands-on leader
• Excellent leader with strong interpersonal skills, and the ability to build and lead high-performing teams
• Interested in working on an early stage project with many challenges to solve and a fast iteration cycle

Before the detail, here's the challenge you'd help us solve.

AI Platform builds the foundations of Datadog's AI efforts. The org is 70+ people organised in three pillars: training and serving (GPU clusters, distributed training, low-level infrastructure), agents (agent harnesses,…

• You have a PhD, MS or equivalent research experience in a scientific field, with strong applied mathematics grounding.
• 6+ years of relevant applied science or ML engineering experience, including setting technical direction for others.
• You have hands-on experience with LLM and agent post-training data: how it is created, managed, and how training-data quality is controlled. This is the requirement that matters most.
• You have real domain expertise in LLMs and agentic applications — not classical ML fine-tuning. Fine-tuning classifiers or traditional models is a different problem from the one this team is solving.

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US.

Before the detail, here's the challenge you'd help us solve.

Before the detail, here's the challenge you'd help us solve.

Fin, now part of Salesforce, is on a mission to help businesses provide perfect customer experiences.

• Experience at AI native companies that train and/or run inference for their own models (e.g. modern AI labs or AI‑native product companies). · preferito
• Experience running training or inference workloads on Kubernetes. · preferito
• Experience with AWS or other major cloud providers. · preferito
• Production experience with Python in ML or infrastructure contexts. · preferito

Fin, now part of Salesforce, is on a mission to help businesses provide perfect customer experiences.

• Experience at AI native companies that train and/or run inference for their own models (e.g. modern AI labs or AI‑native product companies). · preferito
• Experience running training or inference workloads on Kubernetes. · preferito
• Experience with AWS or other major cloud providers. · preferito
• Production experience with Python in ML or infrastructure contexts. · preferito

Help shape the future of AI-driven enablement in financial services

As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy…

• You have depth in distributed computing, RL Infra, and ML systems for training and inference at scale; experience with Ray, Slurm, or similar frameworks is a plus · preferito
• You are proficient in Python, familiar with a systems language (e.g., Rust, C++, or Go), and comfortable with modern cloud and data infrastructure
• You have practical experience implementing and operating ML training and inference systems (e.g., PyTorch or JAX), including containerization, orchestration, and GPU acceleration
• You can explain design and performance trade-offs clearly to both technical and non-technical audiences

Helsing develops artificial intelligence-enabled capabilities to protect and defend democracies. We build Altra, an AI-powered drone software platform, and HX-2, our autonomous drone. We are growing our US operations,…

• Strong proficiency in Rust or C++ for production model deployment and optimization · preferito
• Experience with multiple sensor modalities — particularly infrared or thermal imaging · preferito
• Familiarity with MLOps tooling: experiment tracking (MLflow, Weights & Biases), dataset versioning, model registries · preferito
• Experience with annotation tools and workflows (CVAT, Label Studio, or similar) · preferito

At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we’re building the delivery of (almost) everything and…

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into…

• You have extensive experience designing and implementing deep learning models and agents, with a strong background in distributed training frameworks (e.g., DeepSpeed, Megatron-LM) and ML libraries (PyTorch)
• You have a track record of impactful publications at top-tier venues (e.g., NeurIPS, ICLR, ICML, TMLR)
• You are familiar with efficient training, post-training, and inference techniques for large foundation models
• You can explain complex models and research findings to both technical and non-technical audiences

📍 London, office-first | 🕐 12-month fixed-term contract (with possibility of extension)

📍 London, office-first | 🕐 12-month fixed-term contract (with possibility of extension)

📍 London, office-first | 🕐 12-month fixed-term contract (with possibility of extension)