Software Engineer (Research)

Key Skills

Algorithms, Containerization, Data pipelines, Docker, GraphQL, JavaScript, Kubernetes-K8s, Large scale data processing, Machine learning techniques, MLOps tools, Pandas, Python Programming, Scikit-learn, SciPy

Job Description

We are looking for a Software Engineer (Research) to join our team in London.

Remote applications are also welcomed, provided you're in a similar time zone to the UK.

In this role, you’ll be working directly with our research, engineering and data science teams to help solve some of the most challenging problems facing the construction industry.

Our purpose is to inspire the world to forecast correctly and empower it to tackle risk, powered by our deep learning technology and its unique ability to forecast the outcomes of construction projects. We’re on a mission to change how construction projects are planned, managed and executed, and in the process unlock a trillion dollars of new project value for the world through our data-driven forecasting.

We’re lucky to work on some of the largest infrastructure projects in the world, which gives us both an opportunity and a privilege to make a significant impact on the world around us, and what it will look like in the future, every day.

You’ll be joining a world class and well funded team, backed by top investors including GV (formerly known as Google Ventures) that all believe in the future we are creating. We’ve been on a tremendous growth trajectory for the last four years, and following our latest investment round we’ve got very ambitious growth plans for 2023 and beyond.

About the role:

You will join our newly formed 'nPlan Experimental Research Department' (nerd.nplan.io). In this role, you’ll work in tight collaboration with our diverse research, data science and engineering teams trying to solve the most challenging problems in and beyond machine learning with a potential to revolutionise the construction industry.

• You will own the data & training pipelines enabling researchers to find novel solutions for new problems arising from learning on large construction schedules.
• You will implement state of the art graph algorithms on the world’s largest dataset of construction schedules.
• You will work with researchers implementing, testing and delivering novel machine learning models.
• You will work in a very collaborative environment.

About you:

• Experience implementing high performance processing & algorithms on large-scale datasets (hundreds of millions of data points).
• Comfortable using and operating Unix-based and cloud environments for scripting, experimenting, and ad-hoc reports.
• Familiarity with Python scientific computing tools and libraries, such as SciPy, sklearn, pandas, DVC, or equivalent.
• In the habit of creating good quality code collaboratively, including version control, testing, and review.
• Please mention the word ‘crane’ in your application.

Nice-to-haves:

• Experience implementing ML pipelines & models.
• A track record with graph data and/or optimisation algorithms.
• Familarity with MLOps and cloud tools such as containerisation.

What working at nPlan will be like:

• We are still a relatively small team so there is plenty of opportunity for a high degree of ownership over different areas of the product, and you will be directly exposed to all areas of the business.
• Your voice will always be heard. What you do or say counts, not who you are or where you're from.
• We have three core values that underlie everything we do: Learn from Everything, Be Radically Truthful, and Aim High, Run Fast. These enable us to create a collaborative, inclusive environment where we can move effectively and efficiently to implement the best solutions.
• We are a cross-disciplinary team, and come from all backgrounds and countries. We offer Visa sponsorship and contribute to relocation costs(role dependant).
• Fantastic benefits package for Health & Wellbeing, Learning & Development, family leave, weekly team meals and more.
• We are committed to addressing the diversity problem in the tech industry, and that starts with making sure we have a diverse team where everyone feels at home and can contribute as an equal.
• Having time to yourself and a private life is important. We offer a very flexible work environment and a generous holiday policy.

What your typical work week will be like:

• You will spend most of your time building data pipelines capable of handling hundreds of millions data points.
• You will work closely with the research team, helping with the most challenging engineering tasks.
• You will contribute to our continuous learning efforts in computer science, engineering and machine learning.