AI/ML Researcher

About Fogsphere

Fogsphere is a London-based innovator focused on transforming workplace and urban safety through advanced AI, Computer Vision, and Industrial IoT. Built on a principled “Edge-to-Fog-to-Cloud” architecture, our platform turns passive CCTV cameras and sensors into proactive hazard detectors, capable of identifying threats like missing PPE, fire, smoke, restricted access violations, and more-in real time and at scale. This helps organizations across industries-from manufacturing, construction, oil & gas, and healthcare to smart cities-reduce workplace accidents by up to 90%, ensure regulatory compliance (EHS), and gain powerful operational insights. Fogsphere’s intuitive no-code visual workflows, hyper-scalable Kubernetes-based infrastructure, and commitment to ethical AI and privacy (GDPR compliance) make it a user-friendly yet enterprise-grade solution.

About the Role

We are seeking a highly motivated PhD-level scientist with a strong background in one or several of the following topics:

-Deep Learning

-Generative models with particular emphasis on multimodality

-Active Learning

-Continuous learning

-Face Recognition

-3D/depth estimation

-Explainability and trustworthiness

-In general, deep knowledge on fundamental Machine Learning topics.

You will focus on developing new methods to solve cutting-edge, real-world problems in collaboration with our Research team and, optionally, with academia.

Key Responsibilities

• Lead research lines on some of our different topics listed above.
• Be responsible to create high quality methods that stand-out from off-the-shelve approaches.
• Lead other researchers’ work and participate in a collaborative environment to make sure that the best ideas are explored.
• Be able to communicate and collaborate with engineers and software developers to transitions ideas from prototype to reality. You’re not expected to do any low-level coding, unless you’d wish to do so, but the communication must be good and the organisation of your code too.

Qualifications

• PhD in Computer Vision, Machine Learning, Artificial Intelligence, or related field.
• Solid understanding of one ro more of the topics listed above.
• Publications in international conferences and/or renowned journals.

Preferred Skills (nice-to-have)

• Good software engineering practices: version control (Git), code testing, reproducibility.
• Experience working with MLOps frameworks (e.g., MLflow, Weights & Biases, Kubeflow).
• Knowledge of cloud platforms (AWS, GCP, Azure) for model training and deployment.

What We Offer

• ZERO micromanagement. At Fogsphere, researchers work independently under the Head of Research, with a focus on open discussion and professional development, where the best ideas are the ones applied.
• Opportunity to work on cutting-edge challenges in some of the largest deployments in the field.
• Possibility to publish papers and collaborate with academia on this task.
• Collaborative environment with a team of AI researchers and engineers based on multiple countries.
• Working with academics in the field to help building cutting-edge methods.
• Competitive salary and benefits package.
• Career growth and continuous learning opportunities.