Machine Learning Engineer

Arrive Logistics is a leading transportation and technology company in North America, with plans to continue to significantly grow year over year. Our success is a testament to our remarkable team and what we are building together. 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 has never been a more exciting time to get on board, so read on to learn more and apply today!

As a Machine Learning Engineer at Arrive Logistics, you will play a key role in maintaining and expanding Arrive s ML platform and product capabilities. This role requires driving and contributing to crucial roadmap projects while ensuring quality, maintainability and functionality. These initiatives may vary from serving models scalably to building ML-powered products focused on maximizing profit.

• Design, build, and maintain scalable ML systems and infrastructure using Python, Postgres, and Elasticsearch.
• Partner closely with other Machine Learning Engineers, Product Managers, Data Scientists, Data Engineers, and Product Engineers to ensure the successful delivery of strategic and roadmap initiatives
• Own systems throughout the software development lifecycle, from design to development, deployment and monitoring.
• Maintain and improve performance of existing data systems and processes while balancing maintainability, observability and readability.
• Participate in an on-call rotation where you will support incidents and questions about service behavior from product managers.
• Demonstrate a deep sense of ownership by developing a thorough understanding of a domain. At the same time, you must be able to explain the behavior of and contribute to code bases that may be outside your domain.
• Proactively propose solutions to gaps in process, technology, software design and architecture
• Provide rigorous and detailed code reviews that uphold team standards, testing and software design best practices
• Foster a culture of constant improvement and growth, engineering excellence, humility, positivity and curiosity. Take a lead role in making our two days in the office productive and engaging, fostering face-to-face mentorship and collaborative whiteboarding sessions.

• Bachelor’s degree in Computer Science, Engineering, or a related field or equivalent professional experience.
• 3+ years of experience with ML ops (features stores, model registries and auto ML), model serving and optimization.
• 3+ years of experience with Python and building highly scalable backend services
• Experience with frameworks like Sklearn, Pandas and Numpy. Plus if Huggingface, Tensorflow, Pytorch experience.
• 2+ years of experience with relational databases
• 2+ years of experience designing maintainable and scalable systems
• System design experience with a focus on loosely coupled, distributed systems, microservices and event-driven architectures
• Experience developing cloud-native dockerized applications in Kubernetes
• Experience working with online experimentation and platforms like Statsig
• Understanding of both traditional machine learning and deep neural networks
• Strong communication skills with the ability to articulate, diagram and document complex ML or engineering concepts.
• Strong analytical, problem-solving, decision-making, and interpersonal skills.
• Strong project management and organizational skills with experience identifying project milestones to ensure timely project delivery
• You are a self-starter who can deliver projects independently, yet you also thrive in collaborative environments. You recognize the value of diverse perspectives in developing optimal solutions and consistently demonstrate a willingness to support colleagues as a strong team player.
• You approach software engineering as a craft, balancing the pursuit of clean, maintainable code with the demands of a fast-moving, dynamic business environment. You collaborate effectively with product managers and leadership to choose development paths that minimize technical debt while ensuring the timely delivery of…