ML Engineer: Knowledge Graphs for AI in Construction

ML Engineer: Knowledge Graphs for AI in Construction

Full-Time 40000 - 50000 £ / year (est.) No working from home possible
City, University of London

At a Glance

  • Tasks: Design and develop AI-driven safety systems for the construction industry using knowledge graphs.
  • Company: City, University of London - a global leader in academic excellence.
  • Benefits: Competitive salary, pension scheme, and comprehensive training opportunities.
  • Other info: Join a diverse community committed to equality and inclusion.
  • Why this job: Make a real impact in construction safety with cutting-edge AI technology.
  • Qualifications: Masters or PhD in Computer Science, Python programming, and knowledge of Semantic Web technologies.

The predicted salary is between 40000 - 50000 £ per year.

Founded in 1894, City, University of London is a global university committed to academic excellence with a focus on business and the professions and an enviable central London location. City attracts around 20,000 students (over 40% at postgraduate level), from more than 150 countries and staff from over 75 countries. In the last decade City has almost tripled the proportion of its total academic staff producing world-leading or internationally excellent research. During this period City has made significant investments in its academic staff, its estate and its infrastructure and continues to work towards realising its vision of being a leading global university. The culture at City is built on our shared core values, which means that all employees are expected to behave according to our values: “We care, We learn, We act.”

Background

We seek to appoint a Software Engineer (SE) on a full-time basis for 4 months with an option to extend for 3 months (subject to approval). This role is part of a UK/Singapore project funded by InnovateUK: Safety with Sensor AI and Network Environments for the Construction Industry (Saine-CI), led by Dr Tillman Weyde in collaboration with AITIS Ltd and Iknaia Ltd. The task is to design, develop and evaluate AI driven construction safety systems, that use knowledge graphs in connection with machine learning models applied to camera and sensor data.

Responsibilities

This role is about the design, implementation and evaluation of methods for knowledge based evaluation of machine learning applied to video, audio and other data from construction sites. These methods knowledge representations in OWL and RDF, and practical application evaluation in live environments.

Person Specification

The candidate should have a Masters or PhD in Computer Science or a related subject. Programming skills in Python and experience with Semantic Web technologies as well as some knowledge of logic and knowledge representations required. A combination of these skills as well as a passion for developing AI and knowledge based technology would be ideal.

Additional Information

City offers a sector-leading salary, pension scheme and benefits including a comprehensive package of staff training and development. Closing date: 1st May 2024 at 11:59pm. City, University of London is committed to promoting equality, diversity and inclusion in all its activities, processes, and culture for our whole community, including staff, students and visitors. We welcome applications regardless of age, caring responsibilities, disability, gender identity, gender reassignment, marital status, nationality, pregnancy, race and ethnic origin, religion and belief, sex, sexual orientation and socio-economic background. City operates a guaranteed interview scheme for disabled applicants.

ML Engineer: Knowledge Graphs for AI in Construction employer: City, University of London

City, University of London is an exceptional employer that fosters a culture of academic excellence and innovation, particularly in the field of AI and construction safety. With a commitment to employee development, a sector-leading salary, and a vibrant central London location, City provides a supportive environment where staff can thrive and contribute to meaningful projects. The university's dedication to equality, diversity, and inclusion further enhances its appeal as a workplace for talented individuals from all backgrounds.

City, University of London

Contact Details:

City, University of London Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land ML Engineer: Knowledge Graphs for AI in Construction

Tip Number 1

Network like a pro! Reach out to people in the industry, especially those connected to City, University of London. Attend events, webinars, or even just grab a coffee with someone who works there. Personal connections can make all the difference!

Tip Number 2

Show off your skills! If you’ve got projects or a portfolio that showcases your work with machine learning and knowledge graphs, don’t hold back. Bring it up in conversations or interviews to demonstrate your expertise and passion.

Tip Number 3

Prepare for the interview by diving deep into the specifics of the role. Brush up on your Python skills and be ready to discuss how you’d apply AI in construction safety systems. The more you know, the more confident you’ll feel!

Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the team at City. Don’t miss out on this opportunity!

We think you need these skills to ace ML Engineer: Knowledge Graphs for AI in Construction

Machine Learning
Knowledge Graphs
AI Development
Python Programming
Semantic Web Technologies
OWL
RDF

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the role of ML Engineer. Highlight your programming skills in Python and any experience with Semantic Web technologies. We want to see how your background fits perfectly with our project!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and knowledge-based technology. We love seeing enthusiasm, so let us know what excites you about this role!

Showcase Relevant Projects:If you've worked on projects related to machine learning or knowledge graphs, make sure to mention them. We’re keen to see practical examples of your work that demonstrate your skills and creativity.

Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!

How to prepare for a job interview at City, University of London

Know Your Stuff

Make sure you brush up on your knowledge of machine learning, knowledge graphs, and the specific technologies mentioned in the job description. Familiarise yourself with OWL and RDF, as well as any relevant projects or research that City, University of London has been involved in.

Show Your Passion

During the interview, express your enthusiasm for AI and knowledge-based technology. Share examples of past projects or experiences that highlight your passion and how they relate to the role. This will help you stand out as a candidate who truly cares about the field.

Prepare for Practical Questions

Expect technical questions that may require you to solve problems on the spot. Practice coding challenges in Python and be ready to discuss your thought process. This will demonstrate your problem-solving skills and ability to apply your knowledge in real-world scenarios.

Align with Their Values

City values 'We care, We learn, We act.' Think about how your personal values align with these and be prepared to discuss this during the interview. Showing that you resonate with their culture can make a positive impression on the interviewers.