Machine Learning Engineer II, Navigation API
Machine Learning Engineer II, Navigation API

Machine Learning Engineer II, Navigation API

Full-Time 36000 - 60000 £ / year (est.) Home office possible
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At a Glance

  • Tasks: Design and optimise ML pipelines for Mapbox's Traffic and Movement products.
  • Company: Join Mapbox, the leading platform for real-time location services used by millions of developers.
  • Benefits: Enjoy flexible working hours, remote options, and a supportive work environment.
  • Why this job: Be part of a diverse team making impactful contributions to geospatial data and community projects.
  • Qualifications: Experience in Python, data pipelines, and AWS infrastructure is essential; mentoring skills are a plus.
  • Other info: Opportunities for community engagement and collaboration with academic partners.

The predicted salary is between 36000 - 60000 £ per year.

Mapbox is the leading real-time location platform for a new generation of location-aware businesses. Mapbox is the only platform that equips organizations with the full set of tools to power the navigation of people, packages, and vehicles everywhere. More than 4 million registered developers have chosen Mapbox because of the platform\’s flexibility, security and privacy compliance. Organizations use Mapbox applications, data, SDKs and APIs to create customized and immersive experiences that delight their customers.
Mapbox is the leading real-time location platform for a new generation of location-aware businesses. Mapbox is the only platform that equips organizations with the full set of tools to power the navigation of people, packages, and vehicles everywhere. More than 3.9 million registered developers have chosen Mapbox because of the platform\’s flexibility, security, and privacy compliance. Organizations use Mapbox applications, data, SDKs, and APIs to create customized and immersive experiences that delight their customers.
What We Do
The Telemetry team collects location telemetry from mobile Mapbox SDKs and uses it to improve our map, directions, and travel times, as well as to provide insights into human mobility patterns. To do so, we build and deploy pipelines to process, anonymize, and analyze billions of location probes per day. The customers of our unique, privacy-centric datasets on traffic patterns and human activity range from major corporations to local governments and NGO; but we are also committed to making data accessible to smaller developers, and work on a number of community-driven and open-source projects. We\’re a diverse team of backend engineers, data engineers, and data scientists located around the world, but we work closely together, support each other\’s growth and learning, and share an enthusiasm for deriving interesting and useful insights out of geospatial data.
To see some examples of our work, check out some of our blog posts:

  • Tracking how COVID changed mobility patterns throughout the world
  • Shopping and sunbathing: how America responds to quarantine
  • Tracking retail recovery using Movement data
  • Using Movement data to analyze airport traffic
  • How location data becomes traffic data

What You\’ll Do
As a ML Engineer II, you will be responsible for architecting, building, and maintaining production systems for Mapbox\’s Traffic or Movement products and ML Engine. Your technical contributions will include:

  • Designing and building new ML and data pipelines, as well as optimizing existing ML and data pipelines in Python and Spark/PySpark.
  • Building tools for automated quality assurance and data exploration.
  • Designing and building APIs for delivering data to customers.
  • Leveraging geospatial algorithms to optimize pipelines, as well as creating automated tuning and outlier detection algorithms.
  • Partnering with data scientists to make improvements to our models for determining patterns in movement and/or traffic.
  • Participate in an on-call rotation to ensure our systems remain available to customers 24/7. Team members alternate as the on-call primary responder, which may require immediate response outside normal working hours, including weekends.

Outside of your direct technical contributions you will:

  • Collaborate with other teams within Mapbox to expand use of location telemetry data throughout the company.
  • Mentor colleagues, especially with respect to Spark optimization and best practices.
  • Participate in code and design reviews

There are also ample opportunities to act as an evangelist in the larger community by writing blog posts, engaging with our community partners and journalists to help them make the best use of our data, and collaborating with our academic partners on white papers.
What We Believe are Important Traits for This Role

  • Ability to write approachable, performant code with comprehensive tests and thorough documentation.
  • Excellent communication skills, both written and verbal.
  • Experience building and maintaining data pipelines with large datasets
  • Experience designing & building systems at scale using AWS infrastructure
  • A highly autonomous and self-driven approach
  • A solid engineering foundation with an interest in geospatial data and big data analysis
  • Comfort being vulnerable when you don\’t know the answer, and knowing how to ask for help.
  • Ability to communicate how complex systems work to both engineers as well as customers or business stakeholders
  • Experience & enthusiasm for mentoring teammates, providing technical feedback, and sharing knowledge with others

You may need strong skills in the following areas, which form the foundation of our technical stack. We don\’t expect anyone to be an expert in all areas. However, familiarity with more than two is a bonus, and you should be ready to learn any of them. In the bigger picture, curiosity about spatial data and our planet is highly encouraged, as is mentoring aptitude or experience.

  • Python
  • Experience with distributed processing pipelines (Hadoop, Spark, Airflow, Dask)
  • AWS infrastructure (e.g., S3, EMR, ECS, Athena, Lambda, DynamoDB, IAM)
  • Building secure and stable APIs
  • Experience working with very large datasets – statistical analysis, data quality control, optimizing storage

What We Value
In addition to our core values, which are not unique to this position and are necessary for Mapbox leaders:

  • We value high-performing creative individuals who dig into problems and opportunities.
  • We believe in individuals being their whole selves at work. We commit to this through supportive health care, parental leave, flexibility for the things that come up in life, and innovating on how we think about supporting our people.
  • We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company.
  • We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply.

By applying for this position, you acknowledge that you agree to the Mapbox Privacy Policy which is linked here.
Mapbox is an EEO Employer – Minority/Female/Veteran/Disabled/Sexual Orientation/Gender Identity
#LI-Remote #J-18808-Ljbffr

Machine Learning Engineer II, Navigation API employer: Mapbox

Mapbox is an exceptional employer that fosters a collaborative and inclusive work culture, where employees are encouraged to grow and innovate. With a strong commitment to employee well-being, the company offers flexible working arrangements, comprehensive healthcare benefits, and opportunities for professional development, making it an ideal place for those passionate about geospatial data and machine learning. Located in a remote-friendly environment, Mapbox empowers its diverse team to contribute meaningfully to impactful projects while supporting each other's growth.
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Contact Detail:

Mapbox Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Engineer II, Navigation API

✨Tip Number 1

Familiarise yourself with Mapbox's products and services, especially their Traffic and Movement products. Understanding how they leverage geospatial data will help you articulate your interest and knowledge during discussions.

✨Tip Number 2

Engage with the Mapbox community by following their blog and social media channels. This will not only keep you updated on their latest projects but also provide insights into their company culture and values.

✨Tip Number 3

Brush up on your Python and Spark skills, as these are crucial for the role. Consider working on personal projects or contributing to open-source projects that involve building data pipelines or APIs.

✨Tip Number 4

Prepare to discuss your experience with large datasets and AWS infrastructure. Be ready to share specific examples of how you've optimised data pipelines or built scalable systems in previous roles.

We think you need these skills to ace Machine Learning Engineer II, Navigation API

Proficiency in Python
Experience with Spark/PySpark
Knowledge of AWS infrastructure (e.g., S3, EMR, ECS, Athena, Lambda, DynamoDB)
Ability to design and build data pipelines for large datasets
Experience in building secure and stable APIs
Familiarity with distributed processing frameworks (Hadoop, Airflow, Dask)
Strong understanding of geospatial algorithms
Experience in automated quality assurance and data exploration tools
Statistical analysis skills
Data quality control expertise
Excellent written and verbal communication skills
Mentoring and knowledge-sharing capabilities
Problem-solving skills
Ability to work autonomously and self-driven
Curiosity about spatial data and big data analysis

Some tips for your application 🫡

Understand the Role: Before applying, make sure to thoroughly read the job description for the Machine Learning Engineer II position at Mapbox. Understand the key responsibilities and required skills, especially those related to Python, Spark, and AWS infrastructure.

Tailor Your CV: Customise your CV to highlight relevant experience in building and maintaining data pipelines, working with large datasets, and any previous roles that involved geospatial data or machine learning. Use specific examples to demonstrate your skills.

Craft a Compelling Cover Letter: Write a cover letter that not only outlines your qualifications but also expresses your enthusiasm for the role and the company. Mention how your values align with Mapbox's commitment to diversity and innovation in location data.

Showcase Your Projects: If you have worked on relevant projects, especially those involving machine learning or data analysis, include them in your application. Provide links to any code repositories or blog posts that showcase your work and thought process.

How to prepare for a job interview at Mapbox

✨Showcase Your Technical Skills

Be prepared to discuss your experience with Python, Spark, and AWS infrastructure. Highlight specific projects where you've built or optimised data pipelines, as this is crucial for the role.

✨Demonstrate Problem-Solving Abilities

Expect questions that assess your approach to solving complex problems, especially in relation to geospatial data and big data analysis. Use examples from your past work to illustrate your thought process.

✨Communicate Clearly

Since excellent communication skills are essential, practice explaining technical concepts in a way that non-technical stakeholders can understand. This will show your ability to bridge the gap between engineering and business needs.

✨Emphasise Collaboration and Mentorship

Mapbox values teamwork and mentoring. Be ready to discuss how you've collaborated with others in previous roles and how you’ve contributed to the growth of your teammates.

Machine Learning Engineer II, Navigation API
Mapbox
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  • Machine Learning Engineer II, Navigation API

    Full-Time
    36000 - 60000 £ / year (est.)

    Application deadline: 2027-08-18

  • M

    Mapbox

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