Machine Learning Engineer – Pricing Models & AI Pipelines | E-commerce Optimization

Location: Remote (Strong internet + excellent English communication required)

Profasee is transforming e-commerce with AI-driven dynamic pricing that helps Amazon brands maximize revenue, profitability, and discoverability. Backed by proven founders with multiple exits, we’re on a mission to reinvent how merchants price their products—in real time, at scale.

We’re growing fast and need a Machine Learning Engineer who’s ready to build, experiment, and push the boundaries of what’s possible in pricing optimization.

You’re a builder and problem-solver who thrives on turning raw data into real-world impact. You love taking a business challenge and using ML to crush it. You don’t just write models—you own the full pipeline and make sure it works in production.

You’re curious, hands-on, and unafraid of complexity. You get things done fast and right, and you’re always looking to improve. You know that the best models are the ones that actually deliver results, not just sit in a notebook.

• Design, develop, and deploy machine learning models that optimize pricing for thousands of products daily
• Own the full ML pipeline—data wrangling, feature engineering, model development, deployment, monitoring, and continuous improvement
• Partner with e-commerce experts to understand key drivers of revenue, conversion, and pricing dynamics
• Research and test new algorithms, statistical methods, and best practices to improve prediction accuracy
• Build tools and automation to keep models sharp and adaptive to market changes
• Track model performance, spot drifts, and keep improving
• Write clean, scalable code and contribute to a strong engineering culture
  

• 3–5+ years of experience in ML engineering, data science, or related roles
• Proficient in Python, SQL, and data wrangling
• Real-world experience building, deploying, and monitoring ML models
• Solid grasp of statistical methods and machine learning frameworks
• Ability to translate business problems into technical solutions
• Comfortable owning the full lifecycle of ML products from R&D to production
• Strong analytical mindset and a bias for action
• Experience with AWS cloud services
• Proven track record taking ML projects from idea to production
• Familiarity with libraries like SQLAlchemy, Pydantic, Celery, Scikit-learn, Streamlit, FastAPI, Pandas, object oriented programming and data classes.
• A degree in computer science, mathematics, physics, or data science

• Build game-changing tech in a fast-moving, high-impact environment
• Work alongside industry experts and proven founders
• Full ownership and autonomy—your work will ship and matter
• Remote-first culture with flexibility and trust