Staff Machine Learning Engineer

🕒 January 22

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EDITED

WebsiteLinkedInAll Job Openings

51 - 200 employees

💰 $29M Venture Round on 2020-04

EDITED enables competitor and enterprise retail analysis and automation, empowering buyers, planners, merchandisers, and marketers to grow profits.

📋 Description

• Design, develop, and deploy robust ML systems and multi-model AI agents that solve real-world retail challenges. • Lead the entire lifecycle, including prototyping, deployment, monitoring, and maintenance using modern CI/CD and containerization practices. • Build high-performance data pipelines (ETL/ELT) for both training and real-time inference. • Act as a technical lead for the team, mentoring junior engineers and setting engineering best practices. • Partner with Product Managers and Data Scientists to translate business ambitions into sophisticated technical requirements.

🎯 Requirements

• Strong proficiency in Python and frameworks like PyTorch, TensorFlow, or Scikit-learn • Hands-on experience with modern AI orchestration tools such as LangChain and LangSmith • Proven experience with Docker, Kubernetes, and cloud infrastructure (AWS/GCP/Azure) • Expert-level SQL/NoSQL skills • A Master’s or PhD in Computer Science or a related field, or equivalent experience leading research-heavy engineering projects • You take full responsibility for the health of your models from "code to customer." • You value theoretical excellence but prioritize the delivery of scalable, reliable systems that move the needle for the business. • You rely on empirical evidence and rigorous metrics to evaluate models and inform your architectural decisions. • You can explain complex AI concepts to a non-technical stakeholder just as easily as you can conduct a deep-dive code review with a peer.

🏖️ Benefits

• Flexible working options—including hybrid working, flexible hours and a work from anywhere policy • Enhanced parental leave policy • 25 days annual leave + public holidays (and an extra day for every year at EDITED) • Work from anywhere policy • Season Ticket Loan & Cycle to Work schemes • Health Cash App • Access to an Employee Assistance Programme • Gifts for work anniversaries and big life events • Dog friendly office