The Role
Lead architecture and implementation of ML-driven features (including generative AI/LLMs and optimization) across cloud and mobile. Build production model deployment, CI/CD and experimentation infrastructure, define technical strategy from ambiguous product requirements, and own Agile delivery and technical risk communication while collaborating with Product, Engineering, and Data Science.
Summary Generated by Built In
At PortPro, we are revolutionizing the drayage industry with our premier web-based operating system. As a fast-growing company, we are building out the most comprehensive technology platform to optimize supply chains and make them more efficient. By joining our team at the ground level, you will have the opportunity to be a part of our company's growth and expansion as a global organization, while also making a significant impact on the world. Supply chains are a crucial part of the global economy, and by working to improve them, we are not only solving problems for our own benefit, but for the benefit of society as a whole.
Responsibilities
- You'll lead the architecture design and execution to build machine learning-based solutions in the cloud and on a mobile app. This will include but is not limited to the use of Generative AI/Large Language Models (LLMs),Optimization Problems, building Domain Specific LLMs..
- You will be expected to work full stack across mobile app, cloud services to deliver ML-backed features for customers
- You will identify, invent and follow best practices for deploying ML to the cloud and app.
- Translate ambiguous product definition into detailed requirements, and end-to-end technical strategy docs.
- Define and develop infrastructure to build, release and test updates to underlying ML models in production systems. You will build solutions that let the team quickly experiment while maintaining an exceptionally high quality bar for shipped software.
- You will lead SCRUM/Agile ceremonies to create and execute consistent and timely delivery. You will identify and represent technical risks to the customer experience, or its delivery to senior leaders and stakeholders.
The Work
- You'll work with Production, Engineering, Data Science to plan, design and deliver customer-facing experiences.
- Be hands-on in shaping product, user experience, and team processes to iterate quickly.
- Expect to dive deep into the customer problem.
- This team will develop expertise in building software that directly influences real-world human behavior.
Our team is like family. Working at PortPro, we want you to feel like you are part of the bigger picture, not just working for yourself. We work in a no-drama, no-ego environment We work together and collaboratively to achieve the same goal. We are a team of smart, kind, hard working people. You’ll be surrounded by those that inspire you to bring your best self to work each day.
We're an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
Skills Required
- Experience designing and building production ML systems, including Generative AI and LLM-based solutions
- Full-stack engineering across cloud services and mobile applications
- Experience deploying ML models to production, including infrastructure for release, testing, and experimentation
- Expertise with optimization problems and applying them in product contexts
- Ability to translate ambiguous product definitions into technical requirements and strategy documents
- Experience leading Agile/Scrum ceremonies and representing technical risks to stakeholders
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The Company
What We Do
PortPro is a privately-owned technology company providing an AI-powered transportation management system (TMS) and operational software specifically designed for drayage carriers and freight brokerages. Their platform, including drayOS and PortPro AI, helps these companies automate workflows from delivery order to payment, optimize driver utilization, and recover revenue by plugging operational inefficiencies.
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