Machine Learning Engineer

Description:

The Data Science team at CarTrawler is a team full of highly skilled Data Scientists and Machine Learning Engineers from various backgrounds. We design, develop and deploy high-performing ML solutions for pricing, sorting, fraud detection, and many other areas of the business through our own in-house built tech stack that leverages best engineering practices, external tools such as AWS, Docker, CICD, Kubernetes, Python and the support of other teams around the business.

If you have a desire to deploy your work to the real world and see the business impact immediately, Cartrawler is your best choice!

Independently drive projects to develop software tools to service our Data Science solutions and operations using cutting-edge technologies (e.g. AWS, Docker, Kubernetes, etc.) with the ultimate goal to improve business performance.

Liase and collaborate with business stakeholders and other engineering depts. to define requirements and develop solutions.

Continuously maintain and improve existing tools/services internally developed by DS team

Build efficient CI/CD pipelines and design effective testing/QA/logging and monitoring of tools and services.

Review code changes and pull requests and ensure CT best practices are adhered to in coding and development

Mentor junior ML Engineers by providing support and expertise on Engineering related techniques/skills and to be a point of escalation for them.

• Working closely with relevant stakeholders across the business to identify opportunities and ensure alignment across teams and projects
• Conducting research on Data Science and DevOps to ensure our tech stack is continually improving and aligning with best practices
• Developing industry-leading data science DevOps solutions through:

o Identifying detailed requirements, sources, and structures to support solution development

o Determining the optimal solutions and technologies to use to solve the problem at hand

o Ensuring solutions are implemented with the best engineering practices in mind (CI/CD, unit tests, integration tests, logging, monitoring, etc..)

o Developing scalable solutions that can be integrated into production environments if required

o Collaborating in the development and deployment of proposed solutions to a live environment and tracking the effects in real-time

• 
  Maintaining and enhancing existing DS tools/platforms/infrastructure:

o MVT – An in-house built multi-variate testing platform

o ACDC – Our cloud-based solution for deploying ML to production

o Action Factory – An in-house built automated decision-making tool

o Echo – Our in-house built MLOps pipeline tool

o Several in-house built Python libraries

• Supporting the business with BAU tasks related to tools and services Data Science provide
• Effectively communicate outputs to other team members and the wider business in a concise manner that can be understood by both technical and non-technical audiences
• Developing leading POCs to create breakthrough solutions, performing exploratory and targeted data analyses
• Mentoring and educating junior ML engineers on best practices and ways of thinking
• Good understanding of Software engineering and DevOps practices: Object Oriented Programming, data structure, version control, performance tuning, test-driven development, REST API, Docker.
• Experience using major cloud computing services like AWS, and Azure.
• Expertise in writing well-structured, robust, and readable code in Python
• Expertise with version control systems (git) and modern development workflows (feature branches, pull requests, etc…)
• Expertise in writing unit tests and developing integration tests to ensure the quality of the product
• Knowledge of factors that need to be considered when deploying to production environments (computational complexity, resource requirements, etc...)
• Familiarity with relational (SQL), graph, and NoSQL databases
• Ability to communicate complex tools and technologies in a clear, precise, and actionable manner, both verbally and in presentation format, to a broad variety of functional leaders
• Ability to mentor new colleagues and help them learn the technologies, work ethic, and collaboration style that works at Cartrawler.
• Experience using more advanced ML libraries (TensorFlow, theano, PyTorch etc..) is a plus