Machine Learning Lead

We're SweedPos, a product-driven startup building an all-in-one cannabis retail platform. We’re on the lookout for a Machine Learning Lead 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.

Right now, our total team size is around 180 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.

We’re entering a phase where data will be a key differentiator. As our ML Lead, you’ll drive the strategy, architecture, and execution of our ML initiatives - from recommendation systems to predictive analytics. You’ll have a chance to lead a small ML team (starting with hands-on work), define best practices, and build systems that directly impact the product and business outcomes.

• Own the ML roadmap – work closely with product, engineering, and leadership to align ML initiatives with company goals

• Lead end-to-end development of ML features: from ideation and prototyping to deployment and monitoring

• Design and improve core ML systems, including recommendation engines, time series forecasting, and personalization algorithms

• Build and lead the ML team – take part in hiring, onboarding, and performance management of engineers and data scientists

• Mentor and guide team members, fostering a culture of ownership, learning, and continuous improvement

• Establish standards for model development, evaluation, versioning, and deployment in production

• Collaborate cross-functionally with backend, data, and product teams to deliver scalable and maintainable solutions

• Stay ahead of the curve by evaluating and introducing new tools, technologies, and ML practices

• 4+ years of experience in Machine Learning, including production-level model deployment

• Strong experience with Python and SQL; experience with AWS (especially SageMaker) and Docker is a plus

• Proven track record of owning and delivering ML projects end-to-end

• Experience with modern ML workflows (e.g. MLOps, CI/CD for ML)

• Ability to lead and mentor others while remaining hands-on

• Excellent communication and prioritization skills

• Bonus: experience in retail, personalization, 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 45 minutes) – Quick intro & optional tech screen

• Hiring Manager call (up to 45 minutes) - Deep dive into your ML background

• Technical Interview (up to 1.5 hours) – Deep dive into ML skills