Description:

Profasee is transforming e-commerce with AI-driven dynamic pricing to help Amazon brands maximize revenue, profitability, and discoverability.
The company is looking for a Machine Learning Engineer to build, experiment, and push the boundaries of pricing optimization.
The role involves designing, developing, and deploying machine learning models that optimize pricing for thousands of products daily.
The engineer will own the full ML pipeline, including data wrangling, feature engineering, model development, deployment, monitoring, and continuous improvement.
The position requires partnering with e-commerce experts to understand key drivers of revenue, conversion, and pricing dynamics.
Responsibilities include researching and testing new algorithms, building tools and automation, tracking model performance, and writing clean, scalable code.

Requirements:

Candidates should have 3–5+ years of experience in ML engineering, data science, or related roles.
Proficiency in Python, SQL, and data wrangling is required.
Real-world experience in building, deploying, and monitoring ML models is essential.
A solid grasp of statistical methods and machine learning frameworks is necessary.
The ability to translate business problems into technical solutions is important.
Candidates must be comfortable owning the full lifecycle of ML products from R&D to production.
A strong analytical mindset and a bias for action are required.
Experience with AWS cloud services is preferred.
A proven track record of taking ML projects from idea to production is necessary.
Familiarity with libraries such as SQLAlchemy, Pydantic, Celery, Scikit-learn, Streamlit, FastAPI, Pandas, object-oriented programming, and data classes is required.
A degree in computer science, mathematics, physics, or data science is necessary.

Employees will have the opportunity to build game-changing technology in a fast-moving, high-impact environment.
The role offers the chance to work alongside industry experts and proven founders.
There is full ownership and autonomy in the role, ensuring that the work will ship and matter.
The company promotes a remote-first culture with flexibility and trust.