Senior Machine Learning Engineer
Concirrus is at the forefront of digital transformation in the specialty and automotive insurance markets.
Our talented team worked closely with the insurance community to create Quest. Quest is our expertly designed, intuitive, cloud-based digital underwriting platform built upon cutting edge technical architecture. Quest helps the insurance market seamlessly combine complex datasets, and using AI and machine learning, the platform analyses the data to provide insights to transform the way that underwriters select and price risk.
We believe that the key to delivering state-of-the-art insurance in today’s connected world is data, and we’re continuously evaluating datasets that will add value to our clients.
Concirrus doesn’t just want to see the insurance market survive, we believe that with the right tools, the industry could thrive. Customers rely on our team to deliver:
- Class leading datasets to enhance their understanding of real-time risk
- Streamlined data analysis and automated processes
- Cutting edge risk models driven by the latest developments in AI and machine learning to deliver greater efficiencies
- Transparent insights into the behaviours that correlate to claims
- The latest innovations in technology to help them succeed
- All delivered through beautifully designed web applications
Our product suite does the heavy lifting so that our clients can focus their expertise on innovative risk management and pricing.
We’re data scientists, innovators, entrepreneurs, designers, developers, and insurance specialists. We’re also guitarists, rally drivers, athletes, art collectors and investors. We’re an astonishingly diverse bunch with shared values and this suits the way we work.
With backing from insurance and deep tech investors, and a passionate and driven team based in London and Delhi NCR, we’re looking for exceptional people excited by our vision to help us make it happen.
We are currently seeking a Senior Machine Learning Engineer to join our rapidly expanding Noida based team.
Developing products that solve real problems for our customers is at the heart of everything we do. And we’re on the hunt for an exceptional Machine Learning Engineer to help shape Quest, our dynamic data platform that’s changing the game in commercial insurance.
Reporting to our Director of Data Science, you will enjoy working in a structured team environment. You will be inquisitive, and detail-oriented, with strong experience across the full model deployment lifecycle, from building models to deployment and monitoring. You will enjoy implementing methods to build, save and deploy models whether via automated processes or through APIs. In addition, you like to streamline practices and approaches and create tools for others to reuse.
You’re motivated, inquisitive, and understand the value and potential of modelling to the business. You enjoy a challenge and see the bigger picture of what is to be achieved.
This is an exciting and rewarding role requiring a smart, disciplined and experienced Machine Learning Engineer who is data savvy with a very good technical background in programming, the analysis of data, and the design and creation of modelling pipelines.
- Architect and support the end-to-end modelling pipeline process from calculation of data features through to model deployment in production.
- Write reusable code to streamline the operations across the team and ensure that code is correct.
- Design and build tools to enable the Data Science team to operate more efficiently and improve code reuse and testing.
- Encourage the use of Machine Learning Engineering best practices within the team.
- Implement standardised methods and tools such as Docker to create reproducible environments.
- Encourage and implement the use of testing and TDD and other software development best practices.
- Degree in Computer Science, Statistics, Mathematics, Engineering, Bioinformatics, Physics, Operations Research or related field.
- Strong Python Engineering skills and understanding of best practice software techniques.
- Experience and understanding of the modelling process, from building ML models through to deployment.
- Experience creating scalable ML pipelines and creating production grade code using a range of approaches and tools.
- Experience with model lifecycle management and relevant approaches.
- Experience creating utility tools and Python modules under git according to best practices.
- Experience with the AWS ecosystem, including EMR, Lambda, and S3.
- Strong problem-solving skills.
- Proven ability to effectively communicate results.
- Very good interpersonal skills and ability to work closely with other members of the Data Science and Data Engineering teams.
Nice to have:
- Good understanding of virtual environments, Docker and Kubernetes.
- Experience creating dashboards and monitoring tools.
- Experience processing big data using tools like Apache Spark.
- Experience with API frameworks, particularly in a Python context, such as FastAPI or Falcon.
- Experience with Python web frameworks, such as Django or Flask.
- Knowledge of software engineering practices, such as OOP, SOLID, and TDD.
- Track record of working with cluster computing and distributed systems.
- Experience with command-line scripting, data structures and algorithms.
- Relational database experience.
- Knowledge of system architecture best practices.
- Python and SQL, and preferably exposure to other languages.
- Apache Spark (preferably with PySpark) and Python pandas, numpy, scikit-learn.
- AWS tools, such as EMR and Lambda.
- Git version control.
- Docker and Kubernetes.
- Command line, Linux and bash scripting.
As well as the opportunity to work on projects that you enjoy in an environment you’ll love, we like to look after our team members at Concirrus. Here are some of our perks…
- Flexible, outcome driven, working environment.
- We pay competitively with regular pay reviews.
- Quarterly employee growth review to encourage personal growth.
- Share option scheme so you get to own a piece of the pie.
- Private medical insurance (including dependents).
- Learning & Development fund for all employees.
- 18+ days annual leave (plus public holidays).
- Spacious, modern offices, easily accessible through the Metro.
- Coffee and snacks are all on hand in the office to keep you fuelled.
- Friday FED talks – like TED talks, but you get fed (on us).
- Monthly team drinks, birthday cakes and social events.
- Plus, we’re always on the lookout for creative ways to look after our employees and encourage them to come to us when they have an idea or need.