Machine Learning Engineer



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Mars
Published
15.07.2024
Location
London, United Kingdom
Job Type
Hybrid Working Opportunity
TELECOMMUTE

About Mars:

Mars is a family-owned business with more than $50 billion in global sales. We produce some of the world’s best-loved brands: M&M’s®, SNICKERS®, TWIX®, MILKY WAY®, DOVE®, PEDIGREE®, ROYAL CANIN®, WHISKAS®, EXTRA®, ORBIT®, 5™, SKITTLES®, BEN’S ORIGINAL® and COCOAVIA®. Alongside our consumer brands, we proudly take care of half of the world’s pets through our nutrition, health and services businesses such as Banfield Pet Hospitals™, BluePearl®, Linnaeus, AniCura, VCA™ and Pet Partners™. Headquartered in McLean, VA, Mars operates in more than 80 countries. The Mars Five Principles – Quality, Responsibility, Mutuality, Efficiency and Freedom – inspire our 150,000 Associates into taking action every day towards creating the world we want tomorrow.

Data and Analytics is foundational to our Petcare OGSM and will drive our transformation to a business that is powered by data.

To deliver on this ambition set by this OGSM we require the very highest level of technical / engineering expertise within Global Petcare Data & Analytics

There is a need to expand this high performing team of creative, skilled individuals – to help build out new capabilities and bring fresh ideas to the table

Key Responsibilities

  • Research and develop data science models for stakeholders
  • Design, implement and deploy ELT pipelines for Big Data in Databricks and Azure DevOps
  • Build and maintain CI/CD Azure pipelines for deploying python libraries
  • Build and maintain a suite of automated unit and integration tests
  • Create and maintain feature data tables
  • Deploy ML models into production using Databricks, Azure DevOps using existing deployment framework
  • Collaborate with data scientists, DevOps and data engineers to deliver and maintain models
  • Write and maintain technical documentation

Context and Scope

  • Collaborate closely with data science team to test, refactor and optimize machine learning systems in AML and/or Databricks platform(s)
  • Evaluate business requirements and translate these requests into technical requirements.
  • Actively monitor production for issues and performance and continuously improve frameworks
  • Encourage best practices amongst data scientists

Educational and Professional Qualifications

  • Must have - Degree level OR equivalent demonstrated through work experience
  • Nice to have – Masters / Degree with some computing, scientific, statistical or mathematical component
  • For this role, we hope you have the following skills we require to round out our team:
  • Proficient In Python, PySpark, data science libraries and SQL
  • Excellent with Azure Databricks and related technologies
  • Strong in machine learning frameworks (PyTorch, TensorFlow, etc.) and concepts
  • Well-versed In Azure cloud services for machine
  • Adept at Databricks and Azure DevOps pipelines
  • Very good in data analysis and interpretation
  • Good understanding of software engineering best practices

Nice to Have

  • Experience in GitHub workflows
  • Working knowledge of Azure ML

What can you expect from Mars?

  • Work with over 140,000 diverse and talented Associates, all guided by the Five Principles.
  • Join a purpose-driven company where we’re striving to build the world we want tomorrow, today.
  • Best-in-class learning and development support from day one, including access to our in-house Mars University.
  • An industry-competitive salary and benefits package, including company bonus.

 

Mars is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. If you need assistance or an accommodation during the application process because of a disability, it is available upon request. The company is pleased to provide such assistance, and no applicant will be penalized as a result of such a request.

 

We are proud supporters of Women in Data®.  Connect, engage and belong to the largest free female data community in the UK – visit: www.womenindata.co.uk to join our community
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