Machine Learning Engineer (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Machine Learning Engineer (AI): Building and deploying production-grade ML software and infrastructure for energy sector clients with an accent on scalable architecture and MLOps best practices. Focus on bridging the gap between research and real-world impact by designing robust systems and advising stakeholders on complex technical solutions.
Location: Must be based in or able to commute to London, UK (Hybrid role).
Company
is an AI company that builds and deploys human-centric, responsible AI solutions to transform performance for global customers across various industries.
What you will do
- Build and deploy production-grade ML software, tools, and infrastructure.
- Create reusable, scalable solutions to accelerate the delivery of ML systems.
- Collaborate with engineers, data scientists, and commercial leads to solve critical client challenges.
- Lead technical scoping and architectural decisions to ensure project feasibility.
- Define and implement standards for deploying machine learning at scale.
- Act as a technical advisor to customers, translating complex ML concepts for stakeholders.
Requirements
- Experience operationalizing models using frameworks like Scikit-learn, TensorFlow, or PyTorch.
- Strong Python skills and solid experience in software engineering best practices.
- Hands-on experience with cloud platforms (AWS, Azure, or GCP) including architecture and security.
- Experience with container and orchestration tools such as Docker and Kubernetes.
- Understanding of core ML concepts including probability, statistics, and learning techniques.
- Excellent communication skills to guide technical teams and advise non-technical stakeholders.
Culture & Benefits
- Unlimited annual leave policy.
- Private healthcare and dental coverage.
- Enhanced parental leave and family-friendly flexibility.
- Sanctus coaching for mental wellbeing.
- Hybrid working environment.
Hiring process
- Talent team screen (30 minutes).
- Pair programming interview (90 minutes).
- System design interview (90 minutes).
- Commercial interview (60 minutes).
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