We’re , a product-driven startup building an all-in-one cannabis retail platform. We’re on the lookout for a ML Product Owner to join our team remotely and help us scale and optimize our platform.

At Sweed, we’re reimagining how cannabis retailers operate. Our enterprise-grade platform combines POS, eCommerce, Marketing, Analytics and Inventory Management into a single, seamless solution—eliminating the need for multiple third-party tools.

We believe in simplicity, efficiency, and innovation. That’s why we build for scalability and performance, making life easier for cannabis retailers while driving real business growth.

At Sweed, we believe in the medicinal potential of cannabis. It has been shown to help with chronic pain, anxiety, depression, and many other conditions. Despite the lingering stigma, we see cannabis as a powerful tool for improving lives.

The industry is evolving rapidly, and we’re here to drive that transformation—making cannabis retail more efficient, accessible, and customer-friendly.

We’ve been on the market for 7 years, continuously growing and refining our product.

Our focus is on earning customer trust, which means constantly improving our delivery processes and rolling out new features. At the same time, we navigate the complex legal landscape of the cannabis industry, ensuring our platform remains compliant and future-proof.

Our total team size is over 200 people:

The development team is distributed globally and organized into cross-functional product teams. These teams typically consist of 8–12 members, including front-end and back-end developers, QA specialists, and analysts.
Each team is led by a Team Lead and a Product Owner, ensuring effective collaboration and clear direction.
Meanwhile, our CEO, account managers, and customer success team are based in the USA, working closely with us to align product development with business and user needs.

As ML Product Owner, you’ll shape the ML strategy and connect machine learning capabilities with business and customer impact. You’ll own the ML roadmap, define use cases, prioritize initiatives, and work cross-functionally to ensure ML adds tangible value to our clients and product. You’ll act as the bridge between technical execution and business outcomes.

• Own and prioritize the ML roadmap, aligning with company and product goals.

• Translate business needs into ML use cases: recommendations, personalization, demand forecasting, fraud detection, etc.

• Work with stakeholders (Product, Marketing, Retail Ops, Clients) to identify opportunities for ML to drive measurable outcomes.

• Define success metrics for ML features and track their business impact.

• Collaborate with the ML Tech Lead and engineering team to deliver scalable, production-ready features.

• Communicate ML strategy and progress to leadership and clients, ensuring clarity of value.

• Stay on top of market/industry trends in ML for retail and bring relevant innovations into the roadmap.

• 5+ years of experience in ML, data science, or product roles with ML-heavy focus.

• Strong background in applied ML with a track record of delivering business-impactful solutions.

• Ability to translate business needs into technical requirements and vice versa.

• Excellent stakeholder management, prioritization, and communication skills.

• Experience working with technical ML teams and guiding them toward product outcomes.

• Bonus: experience in retail, personalization, marketing analytics, or regulated industries.

• Proactivity – We love team members who take initiative and provide feedback

• Critical thinking – We value problem-solvers who think beyond just writing code

• Adaptability – Our industry is evolving fast, and we need people who thrive in change

• Salary in USD (B2B contract with the US company)

• 100% remote – We’re a remote-first company, no offices needed!

• Flexible working hours – Core team time: 09:00-15:00 GMT (flexible per team)

• 20 paid vacation days per year

• 12 holidays per year

• 3 sick leave days

• Medical insurance after probation

• Equipment reimbursement (laptops, monitors, etc.)

• Recruiter Call (up to 1 hour)

• Interview with Hiring Manager (1 hour)

• Interview with VP of Operations (30 minutes)

• Interview with VP of Product (up to 1 hour)