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Mid LevelFull-timePythonAWSGCPAzureKubernetesDockerMachine LearningTensorFlowPyTorchAI
Salary Range
$76,500 - $103,500 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Machine Learning Engineer to join Faculty, a company that transforms performance through human-centric AI. You will be instrumental in bringing machine learning out of the lab and into the real world, contributing to scalable software architecture and defining best practices.
Key Responsibilities
- →Building and deploying production-grade ML software, tools, and infrastructure.
- →Creating reusable, scalable solutions that accelerate the delivery of ML systems.
- →Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges.
- →Leading technical scoping and architectural decisions to ensure project feasibility and impact.
- →Defining and implementing Faculty’s standards for deploying machine learning at scale.
- →Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders.
Requirements
- ✓Understanding of the full machine learning lifecycle and experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch.
- ✓Strong Python skills and solid experience in software engineering best practices.
- ✓Hands-on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security.
- ✓Experience with container and orchestration tools such as Docker & Kubernetes to build and manage applications at scale.
- ✓Comfort with core ML concepts, including probability, statistics, and common learning techniques.
- ✓Excellent communicator, able to guide technical teams and confidently advise non-technical stakeholders.
- ✓Ability to thrive in a fast-paced environment and enjoy autonomy to own scope, solve, and deliver solutions.
Benefits
- ★Unlimited Annual Leave Policy
- ★Private healthcare and dental
- ★Enhanced parental leave
- ★Family-Friendly Flexibility & Flexible working
- ★Sanctus Coaching
- ★Hybrid Working (2 days in our Old Street office, London)
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