Machine Learning Engineer

1001
London
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 4+ yearsSkills: ["Communication","Good judgment","Analysis","Cross-functional collaboration"]

Build and productionize machine learning systems from experimentation to reliable deployment. Develop, train, fine-tune, and evaluate ML and deep learning models, including LLMs, multimodal models, agents, and retrieval systems. Translate ambiguous problems into measurable ML tasks, design experiments and evaluation frameworks, analyze failures, and improve performance. Ship end-to-end features with robust inference, data, and evaluation pipelines while collaborating with researchers, engineers, and product teams.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
1001
1001
3 weeks ago

Machine Learning Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 7 hours agoStatus: Live

Job Summary

Build and productionize machine learning systems from experimentation to reliable deployment. Develop, train, fine-tune, and evaluate ML and deep learning models, including LLMs, multimodal models, agents, and retrieval systems. Translate ambiguous problems into measurable ML tasks, design experiments and evaluation frameworks, analyze failures, and improve performance. Ship end-to-end features with robust inference, data, and evaluation pipelines while collaborating with researchers, engineers, and product teams.
Location: London
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Develop, train, fine-tune, and evaluate ML and deep learning models.
  • •Build solutions using LLMs, multimodal models, agents, and retrieval systems.
  • •Design experiments, baselines, and evaluation frameworks; analyze results and model failures.
  • •Improve performance through data and modeling changes, focusing on model quality, reliability, latency, complexity, and cost.
  • •Ship end-to-end ML features from prototypes to production, including inference, data, and evaluation pipelines.

Key Requirements

  • •At least 4 years of experience in machine learning, applied research, or software engineering with substantial ML work.
  • •Strong understanding of ML, statistics, and deep learning fundamentals.
  • •Strong Python skills and experience with modern ML/deep learning frameworks.
  • •Experience with modern LLMs, multimodal models, agents, retrieval systems, fine-tuning, and evaluation.
  • •Ability to take ML problems from formulation and prototyping through production with strong software engineering fundamentals.
Experience:4+ yearsMachine learningApplied research
Skills:CommunicationGood judgmentAnalysisCross-functional collaboration
Tech Stack:PythonLLMsMultimodal modelsAgentsRetrieval systemsFine-tuningEvaluationKubernetesContainersGPU workloadsCloud infrastructure

Company Brief

1001
1001 AI builds AI-powered operational intelligence for complex, data-heavy industries like aviation, ports, energy, and construction. Its platform unifies operational data to predict delays, manage risk, and optimize performance across critical infrastructure and megaproject environments.
Industry: AI & Machine Learning
Company Size: Micro (1 to 10 employees)
Growth: Growth Stage Startup
Funding: Series A
Headquarters: London, United Kingdom
WebsiteLinkedIn