Who We Are

Arrive Logistics is one of the fastest-growing freight brokerage firms in the US, with over $2 billion in annual revenue and plans to grow significantly year over year. 

Technology powers everything we do here, which is why we’re investing $30M per year over the next five years to make ours the absolute best in the industry. Our team is dedicated to innovation, building digital solutions to help our partners do business the way they want to — with a seamless experience powered by tools, integrations and processes designed for efficiency. As one of the few brokerages with a proprietary transportation management system, we leverage our wealth of data to improve processes, provide insights to our partners and deliver unparalleled service. 

We are looking for experienced candidates willing to go above and beyond to build technology products that deliver results for customers and drive our business forward!

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
• 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
• Facilitate 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
• 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

Qualifications

• 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 on or supporting data science projects
• Understanding of data science terminology and the ability to communicate with Data Scientists on highly 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

The Perks of Working With Us

• Take advantage of excellent benefits, including health, dental, vision, and life coverage.
• Invest in your future with our matching 401K program.
• Enjoy the flexibility of a hybrid work-from-home schedule based on position and tenure. 
• Build relationships and find your home at Arrive through our Employee Resource Groups.
• Get recognized through our employee rewards program.
• Leave the suit and tie at home; our dress code is casual.
• Eat for free on Mondays and Fridays…lunch is on Arrive! Snack and lunch options are also available daily.
• Work in the booming city of Austin, TX - we are in a convenient location close to the airport and downtown.
• Park your car for free on site!
• Sweat it out using local gym discounts or with the team at our onsite gym.
• Maximize your wellness with free counseling sessions through our Employee Assistance Program
• Start your morning with a specialty drink from our fully stocked coffee bar, Broker’s Brew.
• Get paid to work with your friends through our Referral Program!
• Get relocation assistance! If you are not local to the area, we offer relocation packages and have a Relocation Specialist who can help you along the way.

Your Arrive Experience

When we say “award-winning culture,” we mean it. We’ve already earned “Best Place to Work” honors from Inc. Magazine (three years in a row!), Austin Business Journal and the Chicago Tribune. We intend on topping many more of those lists in the years to come, but we’re not in it for the trophies. We’re committed to culture because it keeps us connected to each other and invested in our shared success while having a blast along the way. Our employee-founded resource groups create communities within Arrive’s walls, including Women in Logistics, Emerging Professionals, PRISMS, Black Logistics Group, and Salute.