AI Engineer Spring Co-op

Who we are:

Optimal Dynamics is on a mission to automate and optimize the logistics industry through the use of advanced analytics. We are based on more than three decades of R&D at Princeton University and represent the most sophisticated technology ever developed for the logistics industry. Optimal Dynamics is a high-growth early-stage company with ~70 employees (but changing very quickly!) and $56M in funding. 

About the team:

We are a team of bright, kind, and solution-oriented people focused on creating value for our customers. We can solve problems individually, but understand that the best solutions are found when the team brainstorms ideas together. We are excited about balancing the need to deploy new solutions quickly and designing solutions that are secured, reliable, maintainable and scalable for the long run.

Who you are:

• You are a quick learner and excited about learning new technologies
• You thrive in an environment with lots of context and minimal guidance
• You are passionate about automated testing, code/data quality and engineering best practices
• You are adept at communicating and collaborating effectively with others, promoting your ideas as well as being humble when you may be wrong
• You enjoy taking full ownership of projects from conception to production
• You like to work within a small team, collaborating with your colleagues (product manager, designer, data scientist) to ship impactful products

Job Description/Responsibilities:

• In the onboarding stage, senior members of the OR/AI team will get you up to speed on our technologies and help you develop your skill set to the point where you can contribute to the development of cutting edge optimization and AI tools for the logistics industry.
• Work directly with at least one senior AI engineer to support and build out projects

Qualifications:

• Available January-July 2023
• Preferably Junior or Senior pursuing a BS/MS in Mathematics, Computer Science, Operations Research, Industrial Engineering, Electrical Engineering, or related field
• Experience with object oriented programming (preferably in Python)
• Background classwork or experience in probability and statistics
• Interested in machine learning and/or optimization
• Demonstrated ability to troubleshoot complex issues and find resolutions
• Ability to work in a fast-paced environment
• The ideal candidate will be expected to graduate between December 2023 through May 2024

Nice to have:

• Experience with Cloud Computing platforms: Amazon AWS, Microsoft Azure, Google App Engine or similar
• Background in stochastic optimization
• Background knowledge about logistics
• Familiarity with Docker and containerization

Where:

• New York, NY

Benefits:

• $35-40/hr
• The ability to learn directly from leaders in the field of AI and optimization

PLEASE NOTE THERE ARE NO HEALTH, ETC. BENEFITS PROVIDED FOR THIS CO-OP POSITION. Please disregard below. 

Benefits:

• Equity
• Health / Dental / Vision 100% covered for employee and 50% for dependents
• Life Insurance
• Flexible Spending Account (FSA)
• 401(k) match
• Unlimited PTO (vacation, personal days, sick days, jury duty, military leave, bereavement) 
• 11 Holidays
• Paid Parental Leave for all employees
• Fitness Membership reimbursement
• Commuter benefits
• Flexible work from home policy

Optimal Dynamics is proud to be an equal opportunity employer that celebrates diversity and is committed to creating an inclusive workplace with equal opportunity for all applicants and employees. Our goal is to recruit the most talented people from a diverse candidate pool regardless of race, color, ancestry, national origin, religion, disability, sex (including pregnancy), age, gender, gender identity, sexual orientation, marital status, veteran status, or any other characteristic protected by law.

Optimal Dynamics is committed to working with and providing access and reasonable accommodation to applicants. If you require an accommodation, please reach out to careers@optimaldynamics.com once you've begun the interview process. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.