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Senior Machine Learning Engineer

Team

Data Science & Analytics

Location

Bellevue

Senior Machine Learning Engineer

The Opportunity:

Flexport is looking for a creative, technically minded Senior Machine Learning Engineer who is motivated to solve some of the world’s most challenging problems.  

Data is at the heart of our business and as a Senior Machine Learning Engineer, you will work to design, build, and productionize Machine Learning (ML) models and solutions on cloud infrastructure. In concert with data scientists and multidisciplinary product and engineering teams, you will be responsible for production model architecture, and integration and interaction with data engineering pipelines. You will need a strong foundation in software development, infrastructure management, data engineering, and distributed systems to facilitate the development of ML powered software products that deliver data-driven insights seamlessly to end users where they need it, and when they need it. You will help to develop high performing individuals and serve as a technical leader and mentor to others. 

Our product and engineering teams collaborate very closely with our Machine Learning Engineers to share domain knowledge, test hypotheses at scale, and develop promising machine intelligence enabled solutions that can be quickly and widely deployed. We are passionate at providing effortless accessible intelligence, and actionable insights to our end users. 

Our ideal candidate is: self-motivated, highly analytical, has a strong experience with cloud infrastructure, technically excellent at writing code, passionate about delivering solutions for end users coping with real-world business problems, and is experienced with mentoring and up-leveling other individuals on the team.  

You Will:

  • Work collaboratively with product, engineering, and business leaders to find opportunities to improve and enhance our technology products, and processes. 
  • Work with large, and complex data sets. Solve difficult data analysis problems by applying advanced analytical methods as needed. 
  • Architect ML software solutions and develop ML models.
  • Design and develop data processing systems.
  • Develop, orchestrate, monitor, maintain, and optimize ML pipelines and solutions.
  • Deliver compelling data-driven solutions that provide users with key insights when they need it, and where they need it.  
  • Communicate findings to technical collaborators, and business stakeholders through storytelling. 
  • Serve as a go-to expert in a data-related sub-domain and provide actionable feedback as part of machine learning experiment peer reviews.  
  • Drive and hands-on contribute to execution of machine learning model development.  
  • Lead collaborative efforts across different functional, and product teams. 
  • Actively reinforce technical strategy and culture. 

You Should Have:

Minimum Qualifications

  • Master’s degree in computer science, software engineering, or related technical field.
  • Strong programming experience in SQL and one or more of the following languages: C/C++, C#, Java, Python. 
  • Strong experience in one or more of the following: Machine Learning, Natural Language Understanding, Computer Vision, Data Mining, Artificial Intelligence, Convex Optimization, Data Engineering. 
  • Strong experience developing, deploying, monitoring, and maintaining ML solutions in a cloud based environment.  
  • Strong communication and interpersonal skills. Demonstrated ability to communicate with business stakeholders to understand requirements, and present findings and recommendations that demonstrate value.  
  • 5+ years of relevant work experience.

Preferred Qualifications 

  • Ph.D. in computer science, software engineering, or related technical field.
  • Experience with distributed computing and large-scale software systems design.
  • Contribution to research communities via publications in conferences such as KDD, ICML, NeurIPS, and/or code contributions in open source communities such as scikit-learn, CLTK, NLTK, etc. 

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About Flexport:

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.

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 incredibly important 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 designed specifically 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.

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