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.