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# Machine Learning Engineer

- **Company:** Postaladdress
- **Location:** UK (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, C++ (Programming Language), Nvidia CUDA, Software Debugging, Distributed Systems, Python (Programming Language), Machine Learning, Open Source Technology, Software Deployment, Pytorch, Large Language Models, Model Validation, Backend, Kubernetes, Low Latency, Performance Monitor, Machine Learning Operations
- **Published:** September 5, 2026
- **Apply:** https://startup.jobs/senior-machine-learning-engineer-runware-8294197

## About the Role

* Proven experience delivering ML systems to production environments
 * Strong, low-level Python skills and deep hands-on experience with PyTorch
 * Experience working with diffusion models, LLMs, or multimodal architectures
 * Practical experience fine-tuning large models (LoRA, PEFT, adapters, etc.)
 * Experience optimizing inference workloads in GPU environments
 * Strong understanding of model evaluation, experimentation, and monitoring
 * Ability to debug performance, memory, and reliability issues in production
 * Strong systems thinking understanding how ML decisions impact infrastructure
 * High ownership and comfort operating in a fast-paced startup environment

Nice to have

 * Experience with vLLM or custom inference servers
 * Experience with Kubernetes or containerised ML workloads
 * Experience working in high-throughput distributed systems
 * Background in AI media generation (image, video, audio)
 * Experience building internal ML tooling or developer-facing APIs
 * Experience with kernels in CUDA/C++

## Description

As a Senior Machine Learning Engineer, you'll take the lead on critical projects, guiding the end-to-end lifecycle from research and experimentation to production deployment and performance monitoring. Your work will help shape the capabilities of our platform and enhance the experiences of users who rely on our cutting-edge AI technologies.

What You'll Be Doing

 * Integrate open-source and third-party models into our inference platform
 * Lead fine-tuning initiatives (LoRA, adapters, PEFT, domain adaptation)
 * Optimise inference workloads for latency, batching, memory efficiency, and throughput
 * Benchmark model quality vs cost vs performance across modalities
 * Improve inference startup times and stability under high load
 * Build evaluation frameworks and internal tooling for model validation
 * Work closely with Infrastructure and Backend teams on scalable serving systems
 * Monitor production performance and drive continuous optimisation
 * Mentor engineers and help raise the ML engineering bar across the team


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- [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding)
- [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock)
- [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models)
- [Instant KAI Sandboxes with vCluster: Multi-Tenant, Multi-Scheduler GPU Sharing](https://www.wearedevelopers.com/videos/100333-instant-kai-sandboxes-with-vcluster-multi-tenant-multi-scheduler-gpu-sharing)

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