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Machine Learning Engineer at Sweed POS. Location Information: Remote. . Hi there! . We're . SweedPos. ,. a product-driven startup building an all-in-one cannabis retail platform. We’re on the lookout for a . Machine Learning Engineer. to join our team remotely and help us scale and optimize our platform.. About Us. 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.. Why We’re Doing This. 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.. Where We Are Now. 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.. Team Structure. 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.. Why This Role Matters. We believe ML can unlock massive value for our customers - from personalized recommendations to predictive analytics. As our . ML Engineer. , you’ll be part of a small, focused team building the foundation of our ML systems. You’ll work on impactful product features, collaborate with engineers and analysts, and have the freedom to experiment and learn.. What to do in the project?. Develop and deploy ML models. to power features like product recommendations, personalization, and demand forecasting. Work across the ML lifecycle. - from data exploration and feature engineering to model training, validation, and deployment. Collaborate closely with product and engineering teams. to turn business problems into data-driven solutions. Design and maintain robust ML . pipelines. , ensuring models are scalable, testable, and easy to iterate on. Continuously monitor and improve model performance. in production through testing, evaluation, and experimentation. Contribute to technical decisions. , share knowledge with peers, and help evolve best practices in our ML stack. Stay up to date with recent ML advancements. and bring new ideas to the team. What professional skills are important for us?. 2+ years of experience as an ML Engineer or Data Scientist. Strong proficiency in . Python. and . SQL. Hands-on experience with model training, validation, and deployment. Familiarity with AWS (especially SageMaker) and Docker is a big plus. Comfortable working with real-world messy data and iterating quickly. Understanding of model lifecycle and . MLOps. principles is a bonus. Strong communication skills and a desire to work in a fast-paced, product-driven team. What Else Matters?. 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. What We Offer. 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.). Hiring Process. 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. .