Staff/Principal Machine Learning Engineer

at  sennder

Machine Learning (ML) and Artificial Intelligence(AI) are revolutionizing the way of doing business at a global scale. sennder is a European digital freight forwarder with a data-centric problem-solving approach to build the next generation of supply chain and road logistics services. Do you want to help us to shape the future?
We are looking for a Staff Machine Learning Engineer to join our central Machine Learning Engineering teams - as part of sennAI department. The department’s mission is to achieve “Automated & Data-Driven Road Logistics”. We’re a large, diverse and multidisciplinary group of ML&AI engineers, data scientists, backend/frontend engineers and technical product people that are passionate by the new AI-empowered digitalization wave that is changing our world. We want to attract, retain and grow world-class talent to form a incredible group that can provide you the most productive and growth-friendly time of your career.
sennAI purpose is to build proprietary technology that can automate sales, brokerage and other business-related activities. Such automation can enable a flywheel where data acquisition and revenues grow exponentially with one another. The scope of our teams is creating best-in-class predictive analytics services while approaching ML Engineering in an holistic, end-to-end fashion: from best practices in ML modelling until engineering excellence around our MLOps Platform that lifts the developer experience to a different realm.
Every day, we acquire 3M+ new real-time data points (augmenting by the day!) about the road logistics industry in Europe. This data is used to build the future of logistics marketplaces where pricing optimization, load-to-carrier recommendation, load search and network optimization happen in an automated fashion. Can you even imagine where we can go with your help? Let’s #keepOnTrucking… together!

• Define the new state-of-the-art for machine learning engineering in the road logistics services
• Apply data science concepts to solve problems like pricing optimization, load-to-carrier recommendation, load search and logistics network optimization, among others
• Mentor junior to senior engineers, enabling them towards successful & impactful software deliveries
• Review technical roadmaps and deliveries across teams
• Design and develop health and performance monitoring tools (MLOps) of data pipelines and the machine learning services in production
• Lead design reviews with peers and stakeholders to decide amongst available technologies.
• Be hands-on when needed while review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Lead the cross-team alignment effort on technical dependency finding and/or matching, cross-domain architectural design and all-in-all Artificial Intelligence related topics
• Enforce the best principles in ML System Design by balancing the feedback loop on data exploitation and data acquisition, follow the 80/20 ruling, focus on the right metric in every design decision and once a shippable amount of value is created, go live, evaluate, learn and iterate