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Mars UK • London, London, United Kingdom

Machine Learning Ops Engineer

2 days/week at home

Core hours 11–3

Dog friendly

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Job Description

Job Description:

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 Skills:

  • Create and maintain machine learning frameworks with Azure native tools

  • Serve batch and real-time models with varying loads and latencies

  • Administer and maintain Azure DevOps CI/CD pipelines to deploy models, infrastructure and applications on Azure

  • Experience in Azure cloud environments such as AKS, compute clusters, dockers, AML SDK, Azure CLI and storage solutions

  • Provide model monitoring, alerting and dashboarding

  • Evolve framework as new technologies and techniques emerge

  • Degree level OR equivalent demonstrated through work experience

Nice to Have

  • Experience in GitHub workflows and machine learning workflows

  • Experience in Grafana/Prometheus or other machine learning monitoring tools

  • Familiarity with machine learning frameworks (PyTorch, TensorFlow, etc.) and concepts

  • Proficiency in Python, PySpark and SQL

  • Masters / Degree with some computing, scientific, statistical or mathematical component

Role Context & Scope:

  • A technical expert for productionising machine learning products using reusable, customisable frameworks

  • 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 MLOps framework adoption and best practices amongst data scientists

Key Responsibilities:

  • Design and implement Azure Machine Learning workflows to productionize machine learning models across Mars Petcare

  • Develop and automate big data pre-processing, feature engineering, ML model training and deployment using Azure Machine Learning and Databricks

  • Design, develop and maintain custom MLOps frameworks for Mars Petcare use-cases

  • Monitor model performance using relevant tools and proactively identify and address potential issues

  • Collaborate with data scientists and DevOps engineers to deliver and maintain models

  • Take technical ownership of MLOps frameworks

  • Design and deliver models in Azure using a suitable tech stack

  • Encourage MLOps best practices and adoption across the teams

  • Provide support for set up and scale up of ML projects

  • Commitment to actively collecting user feedback and improving frameworks

  • Integrate solutions to Mars tech stack and align delivery with company roadmap

What can you expect from Mars?

  • Work with over 130,000 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.

Company benefits

Open to part-time employees
Open to job sharing
Open to compressed hours
Sabbaticals
Enhanced maternity leave – 26 weeks at 90% pay
Enhanced paternity leave – 26 weeks at 90% pay
24 days annual leave + bank holidays
“Pawternity” leave
Pregnancy loss leave
Bank holiday swaps
Location
94%
Employees are very happy with their working location freedom
Hours
91%
Employees are very happy with the flexibility in the hours they work
Benefits
84%
Employees are very happy with the benefits their company offers
Work-life balance
80%
Employees feel that they can switch off quite easily from work
Role modelling
81%
Employees feel that flexible working is part of the culture
Autonomy
90%
Employees feel they have complete autonomy over getting their work done

Additional employee ratings
(these do not contribute to the FlexScore®)

Diversity
75%
Employees feel that the diversity is good and there are continued efforts to improve it
Inclusion
78%
Employees feel that the culture supports equity and inclusivity well
Culture
86%
Employees feel like it is a really great environment to work in
Mission
84%
Employees feel very excited about and aligned with the company mission
Salary
70%
Employees feel that their salary is good and matches the value they bring

Working at Mars UK

Company employees

4,000 In the UK

Gender diversity (male:female)

57:43

Office locations

London, Slough, Waltham, Castle Cary, Birstall, Plymouth

Hiring Countries

Brazil

France

Netherlands

United Kingdom

United States

Awards & Achievements

1st – Large companies

1st – Large companies

Flexa100 2024
Consumer Goods

Consumer Goods

Industry awards 2023
3rd – Large companies

3rd – Large companies

Flexa100 2023
Retail & Ecommerce

Retail & Ecommerce

Industry awards 2022

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