Senior Engineer

6 months ago

Billund, Denmark The LEGO Group Full time

Job Description

Ready to elevate your Data and MLOps engineering skills? Join our AI + Data Science Organisation as a Senior MLOps Engineer 

In this role, you'll design and construct scalable feature pipelines, automate ML models, and ensure their smooth operation within product teams(s).  As a member of our AI + Data Science Organization, you'll also contribute to developing frameworks and patterns for scalable ML deployment across the enterprise. 

Location will be in our campus in Billund and please note there is no relocation budget dedicated for this role. 

Core Responsibilities 

  • Contribute to the system design, integration architecture, and implementation of Machine Learning solutions in production 

  • Bring excellence in MLOps into the product team(s) you work on, guiding them towards robust solutions and paved paths 

  • Build and automate robust and scalable data and ML model management pipelines 

  • Actively contribute to central initiative around enabling ML at scale, and be an inspiration and sparring partner for your junior colleagues. 

Play your part in our team succeeding 

You will be joining the AI + Data Science Organisation, which is the home of 50 data scientists and engineering colleagues, distributed across our Denmark and UK offices. 

As our Senior Engineer, you will be reporting into the Head of Engineering within the organisation. You will primarily work within cross-functional product teams where you will be primarily responsible for bringing to production different machine learning and AI solutions.  A portion of your time  will also be spent contributing to driving excellence in MLOps, working with the broader competency on building a consistent framework / platform /architecture for taking MLOps to the next level across the organization. 

Do you have what it takes? 

You have background in computer science or relevant field and have equivalent industry experience in software engineering. You come with experience building and deploying solutions on AWS or similar cloud computing SaaS / PaaS platforms. You have excellent collaboration and communication skills.  You are proficient in Python 3 and are familiar with the language ecosystem(s) and packages. In addition, you have: 

  • A development process that is test driven and you are familiar with GitHub and/or GitLab. 

  • Good working knowledge of relational / SQL and non-relational / NoSQL database and building data pipelines 

  • Some experience in operationalizing AI / Machine Learning solutions or are very curious about the space 

 

Some of the nice to haves will include: 

  • Experience in ML experiment, model, and data tracking, coupled with a good understanding of machine learning fundamentals, including features, model design, optimization, and drift, and working in partnership with Data Scientists 

  • Experience with tools and frameworks such as Terraform, PyTorch, MLflow, Airflow, and Databricks for ML training and operationalization is highly desirable.  

  • Prior experience in building data pipelines using data processing tools and frameworks like Spark, Airflow, dbt, etc. 

#LI-BL1 

Applications are reviewed on an ongoing basis. however, please note we do amend or withdraw our jobs and reserve the right to do so at any time, including prior to any advertised closing date. So, if you're interested in this role we encourage you to apply as soon as possible.

What’s in it for you?

Here is what you can expect:

Family Care Leave - We offer enhanced paid leave options for those important times.

Insurances – All colleagues are covered by our life and disability insurance which provides protection and peace of mind.

Wellbeing - We want our people to feel well and thrive. We offer resources and benefits to nurture physical and mental wellbeing along with opportunities to build community and inspire creativity.

Colleague Discount – We know you'll love to build, so from day 1 you will qualify for our generous colleague discount.

Bonus - We do our best work to succeed together. When goals are reached and if eligible, you'll be rewarded through our bonus scheme.

Workplace - When you join the team you'll be assigned a primary workplace location i.e. one of our Offices, stores or factories. Our hybrid work policy means an average of 3 days per week in the office. The hiring team will discuss the policy and role eligibility with you during the recruitment process.

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