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Who We Are

For almost a decade, Arrive Logistics has delivered incredible service throughout the U.S., with a commitment to servicing our customers and exceeding expectations. With more shippers moving freight between Mexico, the U.S., and Canada, we’ve expanded our service offering to include cross-border service. Cross-border shipping logistics has a lot of complexities, multiple parties, multiple languages, and a border separating the pickup and delivery. We’re committed to providing employees with a meaningful work experience and have established an award-winning culture that supports personal and career development in a fun, casual and collaborative environment. There’s never been a more exciting time to get on board with our rapidly-growing cross-border team in Guadalajara, so read on to learn more and apply today!

Who We Want

As a Machine Learning Engineer at Arrive Logistics, you’ll play a key role in delivering highly impactful and revenue-generating data products, insights, and capabilities of our Data and Machine Learning Platform. You’ll work closely with Data Scientists to understand current points of friction in the machine learning lifecycle development process and requirements for the systems surrounding the models they’ve developed. You’ll partner with Data Engineers to define and build platform-level capabilities and infrastructure supporting Data Science and set standards for how we test, run, and monitor machine learning models in production. You’ll work with Application and Platform Engineers to adopt and expand on existing Software Engineering and DevOps practices used to deploy our models to production.

You’ll sit within the Data Organization supporting internal technology powering Arrive Logistics in the fast-paced freight industry. If you’re looking to influence data-driven decision making and automated machine learning systems alongside industry experts and a passionate, supportive team, read on. 

What You’ll Do

• Work with a team of Machine Learning Engineers to execute on roadmap items and strategic initiatives for Machine Learning Platform components and capabilities such as experimentation frameworks, model monitoring, artifact versioning, feature stores. 
• Deploy and monitor infrastructure supporting our machine learning model deployments and development environments
• Build batch and real-time pipelines for feature engineering and understand when to use each implementation
• Build APIs and Services using Python to expose the output of our machine learning models via endpoints and message queue systems
• Facilitate and test machine learning model deployments through different environments and coordinate dependencies across Data Science, Data Engineering, and Product Engineering teams
• Implement and document team standards and machine learning operations (MLOps) best practices that have a broad impact on Data and Engineering teams
• Propose and execute on strategies for reducing the gap between building models in a development environment and running them in production
• Implement monitoring and alerting frameworks to ensure data quality in our feature engineering pipelines and machine learning deployments
• Develop Python libraries, functions, and other shared components that enable easier sharing of resources across many Data Science teammates and machine learning models
• Take part in an on-call rotation to respond to and resolve incidents relating to our machine learning systems
• Participate in team Scrum ceremonies to scope new work and provide status updates, demo, and discuss in-progress and completed work

• 2+ years of experience in a data engineering, software engineering, DevOps, or similar role
• 2+ years of experience developing in Python and SQL
• 1+ years of experience working with a major cloud provider such as Azure, AWS, or GCP
• 1+ years of experience working on or supporting data science projects
• Fluency in English and Spanish
• Understanding of data science terminology and the ability to communicate with Data Scientists on technical machine learning projects
• Understanding of the machine learning lifecycle development and deployment process
• Experience managing infrastructure of machine learning platforms or systems running operational machine learning models
• Understanding of common data architectures, processes, and paradigms such as data warehousing/modeling, ETL/ELT, feature engineering, batch vs streaming pipelines
• Ability to articulate, diagram, and document technical data science and engineering concepts 
• Experience with industry-standard Data and Machine Learning Platform technologies such as data warehouses, workflow orchestration platforms, database replication platforms, data quality frameworks, feature stores, data science notebooking tools, etc.
• Experience or familiarity working in agile frameworks

• Get recognized through our employee rewards program.
• Take advantage of our benefits including monthly grocery vouchers, vacation days and more.
• Leave the suit and tie at home; our dress code is casual.
• Eat for free on Mondays and Fridays…lunch is on Arrive! 
• Work in our new Guadalajara office located in Midtown WeWork Plaza 
• Park your car for free on site!
• Maximize your wellness with free counseling sessions through our Employee Assistance Program
• Start your morning with complimentary coffee and tea
• Get paid to work with your friends through our Referral Program!

Your Arrive Experience 

Our award-winning company culture is designed with you in mind. We are committed to supporting your personal and professional growth and making Arrive a place we all love to work.