- Experience designing and implementing ML models and maintaining relevant data in a cloud environment
- Experience working with DevOps to enable your team access to the tools they need
- Contributing to every part of the machine learning product lifecycle
- Proven track record of implementing data engineering best practices in all aspects of the data pipeline, i.e. ETL, data integrity, and monitoring
- Demonstrable proficiency with Python, dbt, SQL, and modern ML tooling
- Experience working with large-scale data model refactoring for better performance, interpretability, and maintainability
- Experience with version control tools (GitHub, GitLab) and Agile methodologies.
- Bachelor's Degree in a quantitative field such as Physics, Engineering, Computer Science, or demonstrated equivalent quantitative experience.
- Excellent communication skills to effectively collaborate with different teams within the engineering org
- Collaborate closely with our engineering, analytics, and data science teams as we take our machine learning projects and infrastructure to the next level
- Right at the start you will be contributing to existing ML projects, creating and maintaining the data pipelines they need, and communicate the results to the organization
- You will own all of the data and ML processes you create
- You will become the expert on our machine learning and data infrastructure and make critical decisions in our path forward
- You will have the opportunity to grow your skill set and take part in projects at the forefront of GenAI, ML, and data science in the logistics industry
- Enjoy working remotely with the added perk of a home office reimbursement
- Unlimited Paid Time Off (PTO)
- A robust healthcare package that includes medical, dental & vision benefits, short-term and long-term disability, AD&S coverage, and flexible/health savings accounts
- 40K program where Shipwell matches up to 4%
- A yearly learning and development budget
- Subsidized internet, cell phone, fitness, and educational reimbursements
- Virtual team-building events where fun and connection take center stage
- Join a vibrant, inclusive workplace shaped by friendly, talented individuals
- Receive a technology package including a MacBook Pro
- Employee Recognition Program to celebrate and incentivize hard work and success
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Machine Learning Engineer - Austin, United States - Shipwell
Description
Job Description
Job DescriptionMachine Learning Engineer
About Shipwell
At Shipwell, we empower supply chain efficiency and service effectiveness at scale. The Shipwell platform includes capabilities previously out of most shippers' technical reach and affordability today. Our solution combines everything shippers need, from transportation management and visibility to procurement, in a comprehensive, easy-to-use platform. It will adapt and scale as market and business demand change, allowing shippers to operate, manage, and optimize the shipping process seamlessly. Industry experts have recognized Shipwell's traction in the market and have differentiated Shipwell as a leader in the logistics industry. Awards include Gartner Magic Quadrant for TMS 2023, 2022, 2021, Food Logistics' 2022 Top Software & Technology Providers, and FreightWaves' FreightTech 2022 and 2021 Awards for Innovation and Disruption in Freight Industry. Shipwell was also named the fourth fastest-growing company in North America on the 2021, 2022, and 2023 Deloitte Technology Fast 500 and Forbes 2020 Next Billion-Dollar Startup.
Our Culture
Shipwell is a fast-paced, high-energy start-up that strives to build the future of shipping every day. Diversity of thought and cross-department collaboration is very important to us. We deliver open, honest, careful communication and work as hard as we play. We create & deliver solutions that are revolutionizing the industry, which brings excitement and purpose to our work. If you are looking for a place that will help you tap into your best work-self and give you hands-on experience building something big, then we invite you to come and build the future of shipping with us
About the Role
As a Machine Learning Engineer, you will contribute to the design, development, and maintenance of data pipelines, optimizing how we use AWS and other cloud infrastructure, and enabling data access for our various research projects. Your responsibilities will encompass extracting, transforming, and loading (ETL) data from various sources, developing and executing data integrity standards, and optimizing performance. You will collaborate closely with cross-functional teams and contribute to the development of scalable and efficient data architectures. This role provides a dynamic opportunity to leverage your expertise in data engineering and learn more about the data infrastructure at Shipwell. This will enable you to drive insights and support data-driven decision-making within our organization.
What we're looking for:
Why Shipwell:
Please note that Shipwell is not offering sponsorship for work visas for this position.
The Salary Range for this role is between $100,000 - $130,000/year. Compensation is based on a number of factors including market location, job-related knowledge, skills, and experience.
Shipwell is an equal opportunity employer and welcomes all qualified applicants regardless of race, ethnicity, religion, gender, gender identity, sexual orientation, disability status, protected veteran status, or any other characteristic protected by law. We celebrate diversity and believe that experience comes in different forms. Diversity in our team makes for better problem-solving, more creative thinking, and ultimately a better product and company culture.
Even more important than your resume is a clear demonstration of impact, dedication, and the ability to thrive in a fast-paced and collaborative environment. Shipwell strives to have an inclusive work environment; so if you are hard-working & good at what you do then please come as you are. We want you to contribute, grow, & learn at Shipwell.
We are looking forward to adding new perspectives to our team
For more information about Shipwell visit , or connect with us on Twitter @shipwell, LinkedIn, and