Flexport is looking for a creative, technically-minded Machine Learning Scientist (MLS) who is motivated to solve some of the world’s most challenging ML problems in global trade.
Data is at the heart of our business, and as a Machine Learning Scientist, you will work to evaluate and provide insights into our physical and digital products. In collaboration with multidisciplinary product, engineering, user experience, and business/operations teams, you will apply advanced Machine Learning (ML) methods to deliver data-driven insights and automated decision solutions in Flexport’s freight forwarding products.
Our business, product, and engineering teams collaborate closely with our Machine Learning Scientists to share domain knowledge, test hypotheses at scale, and develop promising solutions that can be quickly and widely deployed. In addition, we are passionate about providing effortlessly accessible intelligence and actionable insights to our end users. Thus, the ideal MLS candidate is: self-motivated, highly analytical, technically excellent at writing code, and passionate about delivering cutting-edge solutions.
- Work collaboratively with product, engineering, and business to:
- Find opportunities to improve and enhance our forecasting technology products.
- Understand Flexport’s business and operations processes to identify impact opportunities.
- Translate ambiguous business requirements into the right technical solution.
- Design and build robust and scalable production forecasting solutions.
- Perform R&D of new ML models and refactor ML solutions to support scalable production deployment.
- Explore and work with large and complex data sets to implement robust feature and signal extraction models to identify signals that support better decision-making.
- Deliver compelling data-driven estimation solutions to support automated decision-making at scale.
- Research prior work to inform and develop rational hypotheses and quantify appropriate metrics & targets.
- Work collaboratively with other scientists (e.g., operations research, optimization) to develop hybrid solutions that combine machine learning and optimization to automate decision-making.
- Develop prototype data analysis/machine learning pipelines iteratively as needed to generate actionable insights.
- Communicate findings to technical collaborators and business stakeholders.
- Perform requirements gathering and data analysis.
You Should Have:
- Masters degree in quantitative fields (e.g., computer science, mathematics, statistics, physics, engineering, etc.)
- Experience and strong technical background in one or more of the following: Machine Learning, Natural Language Understanding, Computer Vision, Data Mining, Artificial Intelligence, Numerical Optimization, Data Engineering.
- 3+ years of industry experience building, iterating, validating, and deploying statistical and/or machine learning models.
- Software development experience using general-purpose programming languages like Python, Java, or C/++, C#
- Experience working with large data sets.
- Strong verbal and written communication.
- Experience training Machine Learning models on libraries such as Tensorflow, PyTorch, Scikit-learn.
- Ph.D. in quantitative fields (e.g., computer science, mathematics, statistics, physics, engineering, etc.)
- A strong theoretical background in machine learning/artificial intelligence, algorithms, distributed systems, or statistics.
- Experience training machine learning models in a cloud computing environment like Amazon EC2, Google Cloud Platform, Microsoft Azure, etc.
- Experience in machine learning and statistical techniques such as classification, clustering, regression, statistical inference, collaborative filtering, and experimental design.
- Experience taking research prototypes to production.
- Some knowledge of the transportation and logistics industry.
- Proven object-oriented design and implementation skills (Python, Java, and C++),
- Strong research track record with contributions to research communities via publications in top conferences and journals and code contributions in open source communities such as scikit-learn, CLTK, NLTK, etc.
We believe global trade can move the human race forward. That’s why it’s our mission to make global trade easier for everyone. We aim to do this by building the Operating System for Global trade - a strategic model combining advanced technology and data analytics, logistics infrastructure, and supply chain expertise. Flexport today connects almost 10,000 clients and suppliers across 109 countries, including established global brands like Georgia-Pacific as well as emerging innovators like Sonos. Started in 2013, we've raised over $1.3B in funding from SoftBank Vision Fund, Founders Fund, GV, First Round Capital, and Y Combinator. We’re excited about the three big ways we’re moving forward after our recent $1B investment from SoftBank Vision Fund in February 2019.
Are you worried about not having any freight forwarding experience?
- Don’t be! We’re building the first Operating System for Global Trade. That’s why it’s crucial for us to bring people from diverse backgrounds and experiences together with our industry veterans to help move the freight forwarding industry forward.
- What’s freight forwarding, and why does it matter? Freight forwarding is the coordination and shipment of goods from one place to another, and it’s what makes global trade possible. Flexport is on a mission to make global trade easier for everyone because we believe it can help connect the world and break down economic barriers.
- We know this industry is complex. That’s why we invest in education starting day one with Flexport Academy, a one-week intensive onboarding program explicitly designed to set every new Flexport employee up for success.
At Flexport, our ability to fulfill our mission of making global trade easy for everyone relies on having a diverse, dedicated, and engaged workforce. That is why Flexport is committed to creating and nurturing an environment where anyone can be their authentic self. All qualified applicants will receive consideration for employment regardless of race, color, religion, sex, national origin, age, physical and mental disability, health status, marital and family status, sexual orientation, gender identity and expression, military and veteran status, and any other characteristic protected by applicable law.