Join Our Team as a Machine Learning Engineer in the Energy Transition & Environment Sector

About Faculty

Faculty is at the forefront of transforming organizational performance with safe, impactful, and human-led AI solutions. As Europe’s leading applied AI company, Faculty has paved the way in the AI domain, long before it became a buzzword. Our origins trace back to 2014 with the introduction of our Fellowship program, aimed at nurturing academics into commercial data scientists. Today, we support over 300 global clients across sectors like retail, healthcare, energy, and government with cutting-edge software and tailored AI consultancy solutions. Our dedication to safety and excellence has earned us the privilege of becoming OpenAI's first technical partner, aiding customers in deploying state-of-the-art generative AI responsibly.

Our high-impact AI applications have made significant contributions by forecasting NHS demands during the COVID pandemic, enhancing green energy production, optimizing marketing expenditures, and safeguarding children online. At Faculty, we recognize AI as a revolutionary technology and are keen on expanding our team with talented individuals who are committed to harnessing its vast potential responsibly.

What You'll Be Doing

As a Machine Learning Engineer, you will be instrumental in designing, building, and deploying production-grade software, infrastructure, and MLOps systems. Your work will focus on solving diverse, high-impact challenges particularly in the Energy Transition & Environment sector. Holding an engineering-centric mindset, you'll bring cutting-edge ML applications to life, create innovative methodologies, advocate for best AI management practices, and collaborate with a spectrum of both technical and non-technical stakeholders.

Key Responsibilities:

• Develop scalable and reusable tools for better delivery of ML solutions.
• Collaborate with customers to refine their needs into actionable AI strategies.
• Partner with data scientists and engineers to pioneer best practices and new technologies in AI.
• Contribute to Faculty’s vision of operationalizing ML software.
• Engage in cross-functional teams consisting of engineers, data scientists, designers, and managers to deliver technically sophisticated AI systems.

Who We're Looking For

We value individuals at Faculty not just for their technical skills but also for their attitude and ability to enhance our organizational culture. Ideal candidates are those who:

• Think critically and scientifically, constantly testing assumptions and seeking evidence.
• Are innovatively resolving traditional challenges and consistently enhancing professional growth.
• Maintain a pragmatic and outcome-oriented approach, capable of realizing ideas into tangible solutions.

Technical Requirements:

• Proficiency in the full machine learning lifecycle using frameworks like Scikit-learn, TensorFlow, or PyTorch.
• Solid understanding of probability, statistics, and both supervised and unsupervised learning techniques.
• Experience in programming with Python and familiarity with cloud infrastructure, security, deployment, and open-source tools.
• Knowledge of container technologies such as Docker and Kubernetes.
• Comfortable working in a dynamic, high-growth startup atmosphere.
• Excellent verbal and written communication skills.

If you are excited about making a considerable impact using AI, and possess the skills and drive to transform ideas into real-world solutions, we would love to hear from you.

Apply now to become a part of our journey at Faculty and help us navigate the exciting terrain of AI innovation in the Energy Transition & Environment space!