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Staff Machine Learning Engineer
JOB SUMMARY
Roles
ML/AI Engineer
Skills & Technologies
Languages:PythonSQL
ML/AI:TensorFlowPyTorchscikit-learnLangChain
Cloud/DevOps:AWSAzureGCPDockerKubernetes
Tools:CI/CD
Job details
As a Staff Machine Learning Engineer at EDITED, you will be a driving force behind our AI strategy, building complex, production-ready AI agents and scalable systems.
You will take full ownership of the ML lifecycle and lead the entire lifecycle, including prototyping, deployment, monitoring, and maintenance using modern CI/CD and containerisation practices.
RequirementsML Fundamentals: Strong proficiency in Python and frameworks like PyTorch, TensorFlow, or Scikit-learn, with a deep understanding of NLP, deep learning, or reinforcement learning. Agentic AI: Hands-on experience with modern AI orchestration tools such as LangChain and LangSmith. Production Excellence: Proven experience with Docker, Kubernetes, and cloud infrastructure (AWS/GCP/Azure), with a focus on scaling models in production. Data Fluency: Expert-level SQL/NoSQL skills and the ability to design high-performance pipelines for massive datasets. Academic/Practical Background: A Master’s or PhD in Computer Science or a related field, or equivalent experience leading research-heavy engineering projects.
BenefitsEnhanced parental leave policy25 days annual leave + public holidays (and an extra day for every year at EDITED)Work from anywhere policySeason Ticket Loan Cycle to Work schemesHealth Cash AppAccess to an Employee Assistance ProgrammeGifts for work anniversaries and big life eventsDog friendly office.
You will take full ownership of the ML lifecycle and lead the entire lifecycle, including prototyping, deployment, monitoring, and maintenance using modern CI/CD and containerisation practices.
RequirementsML Fundamentals: Strong proficiency in Python and frameworks like PyTorch, TensorFlow, or Scikit-learn, with a deep understanding of NLP, deep learning, or reinforcement learning. Agentic AI: Hands-on experience with modern AI orchestration tools such as LangChain and LangSmith. Production Excellence: Proven experience with Docker, Kubernetes, and cloud infrastructure (AWS/GCP/Azure), with a focus on scaling models in production. Data Fluency: Expert-level SQL/NoSQL skills and the ability to design high-performance pipelines for massive datasets. Academic/Practical Background: A Master’s or PhD in Computer Science or a related field, or equivalent experience leading research-heavy engineering projects.
BenefitsEnhanced parental leave policy25 days annual leave + public holidays (and an extra day for every year at EDITED)Work from anywhere policySeason Ticket Loan Cycle to Work schemesHealth Cash AppAccess to an Employee Assistance ProgrammeGifts for work anniversaries and big life eventsDog friendly office.
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EDITED United Kingdom