Machine Learning Engineer

Summary

Join SweedPos, a product-driven startup, as a Machine Learning Engineer to contribute to scaling and optimizing our all-in-one cannabis retail platform remotely. You will develop and deploy ML models for features like product recommendations and demand forecasting, working through the entire ML lifecycle. Collaborate with product and engineering teams to create data-driven solutions, design robust ML pipelines, and continuously monitor model performance. Contribute to technical decisions, share knowledge, and stay updated on ML advancements. This role offers the opportunity to work on impactful product features within a small, focused team.

Requirements

• 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
• Comfortable working with real-world messy data and iterating quickly
• Strong communication skills and a desire to work in a fast-paced, product-driven team

Responsibilities

• 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

Preferred Qualifications

• Familiarity with AWS (especially SageMaker) and Docker is a big plus
• Understanding of model lifecycle and MLOps principles is a bonus
• 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

Benefits

• 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.)