Senior Machine Learning Engineer

Runware
United Kingdom
Workplace: RemoteFull timeFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Mentoring","High ownership","Collaboration","Continuous optimization","Benchmarking"]

Lead end-to-end ML engineering for an AI media creation platform, from research and experimentation through production deployment and performance monitoring. Integrate open-source and third-party models, drive repeatable fine-tuning (LoRA/PEFT/adapters), and optimize inference workloads for latency, batching, memory, and throughput. Benchmark quality vs. cost, build evaluation and validation tooling, collaborate with infrastructure and backend teams, and mentor engineers to raise the ML bar.

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FursaFursa
Runware
Runware
6 months ago

Senior Machine Learning Engineer

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 6 hours agoStatus: Live

Job Summary

Lead end-to-end ML engineering for an AI media creation platform, from research and experimentation through production deployment and performance monitoring. Integrate open-source and third-party models, drive repeatable fine-tuning (LoRA/PEFT/adapters), and optimize inference workloads for latency, batching, memory, and throughput. Benchmark quality vs. cost, build evaluation and validation tooling, collaborate with infrastructure and backend teams, and mentor engineers to raise the ML bar.
Location: United Kingdom
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Integrate open-source and third-party models into the inference platform.
  • •Lead fine-tuning initiatives (LoRA, adapters, PEFT, domain adaptation) and drive reusable, repeatable workflows.
  • •Optimize inference workloads for latency, batching, memory efficiency, and throughput.
  • •Benchmark model quality vs. cost vs. performance across modalities and improve startup time and stability under load.
  • •Build evaluation frameworks and internal tooling, collaborate with Infrastructure/Backend teams, monitor production performance, and mentor engineers.

Pay and Benefits

Perks:Paid LeaveEquityRemote WorkFlexible HoursParental LeaveCompany Retreats

Key Requirements

  • •Deep, hands-on expertise in Python and PyTorch for ML workloads, including edge cases beyond standard framework usage.
  • •Experience building ML applications/models yourself (not just deploying existing ones), with verifiable project history (e.g., GitHub).
  • •Hands-on GPU-level work writing kernels in CUDA/C++ or Triton.
  • •Low-level experience with model internals (e.g., diffusion model architectures such as diffusers) and PyTorch compiler (torch.compile) or similar tools.
  • •Repeatable fine-tuning of large models as a service (LoRA/PEFT/adapters), with high ownership in a fast-paced startup environment.
Experience:AI media generationMultimodalStartupsMachine learning
Education:Bachelor's
Skills:MentoringHigh ownershipCollaborationContinuous optimizationBenchmarking
Tech Stack:PythonPyTorchCUDAC++TritonTorch.compileLoRAPEFTAdaptersDiffusersVLLMKubernetesDockerGPU kernelsCUDA kernelsInference

Company Brief

Runware
Runware.ai offers a platform for building, deploying, and managing LLM-powered applications, focusing on orchestration, observability, and operational tooling to ensure reliable, scalable, and safe production AI workflows.
Industry: Developer Tools
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