Python Job: Machine Learning Engineer

Job added on

Location

Shannon - Ireland

Job type

Full-Time

Python Job Details

Job Description



REQ ID: 113034
JOB TITLE: Machine Learning Engineer
SALARY: Competitive
LOCATION: Shannon, Ireland

Dreaming for tomorrow is about more than ideas and ambitions. We-re already building the next generation of vehicles, using repurposed and brand-new technology and techniques. We-re doing more than dream, we-re creating the future of mobility and automotive for years to come.

What To Expect

This is an excellent opportunity for a Machine Learning Engineer to join our team at an extremely exciting and crucial time for the organisation. It is a brilliant opportunity to join a household name automotive brand that-s strengthening its engineering department in the area of machine learning & data driven decision making.

The Machine Learning Engineer will be using cutting-edge technologies and Machine Learning techniques to process, creatively analyse and model large volumes of complex data. The individual will be exposed to a wealth of different topics as diverse as NLP, clustering, timeseries, Explainable AI and bespoke model development. The insights gained will support new product and feature development, advance our operations and contribute to a host of exciting new projects.

Key Accountabilities and Responsibilities
  • Conceptualize, build and help maintain state-of-the-art ML/AI systems in the team.
  • Develop value-adding models and algorithms, helping to deliver operational solutions where appropriate.
  • Work with product teams and stakeholders to identify problem statements which can be solved using data science, machine learning and the automation of process.
  • Stay up to date with the latest trends in the field of Machine Learning.
  • Share knowledge with others through regular knowledge share sessions.
  • Document ML systems, configurations and results.
  • Work in an agile development manner and champion a data-driven culture.

Key Performance Indicators
  • Writing high quality, simple and scalable code, with clear intent to other engineers and the machines running the systems.
  • Compliance of machine learning projects with Jaguar Land Rover data governance and privacy by design requirements throughout the engineering lifecycle.
  • Reusable ML artifacts produced - frameworks, datasets, models etc.
  • Completion of tasks to agreed timing, cost and quality, and in line with vehicle programme timing requirements.

What You Will Need

Essential
  • Broad knowledge of key concerns in Machine Learning, AI and related areas.
  • Practical experience with machine learning techniques, e.g. classification or regression.
  • Experience using Python (or R) and optionally another high-level language.
  • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, caret, dask (or similar).
  • Experience writing and testing code within software development environments.
  • Experience with various data cleansing and data preparation techniques on large datasets.
  • Good written and verbal communication and problem-solving capabilities.
  • Degree in Computer Science, Statistics, Mathematics, or another quantitative discipline (Master-s or comparable level of experiences is an asset)

Desirable


  • Knowledge of Linux/*nix family of operating systems.
  • Experience with cloud computing/platforms (e.g. Google Cloud Platform, AWS).
  • Knowledge or experience of data privacy by design and data management best practice.
  • Experience or interest in Explainable AI / model interpretability.
  • Experience deploying and maintaining models in production.

SO WHY US?

Bring all this to the home of premium innovation, and you-ll find the opportunities to further your career with a world-class team, a discounted car purchase and lease scheme for you and your family, membership of a competitive pension plan and private medical cover. All this and more makes Jaguar Land Rover the perfect place to continue your journey.

Jaguar Land Rover is committed to equal opportunity for all.