TrustScale, an e2f company
Leading the future of AI data services with trustworthy, high-quality solutions that power innovation for brands worldwide.

Role Summary

We are seeking a Data Engineer with strong Python skills and experience in modern ML frameworks. You will support the development and optimization of AI models, collaborate with an international team, and continuously learn and iterate under senior guidance. This role is ideal for someone who thrives in a dynamic, distributed environment and is eager to grow in the AI field.

Responsibilities

• Develop and refine AI and ML models to support product and business needs.
• Adapt and enhance existing codebases under guidance from senior team members.
• Prototype, test, and iterate on models quickly to reach production-quality outcomes.
• Conduct exploratory data analysis and derive actionable insights from large datasets.
• Collaborate with cross-functional teams to align AI solutions with business requirements.
• Deploy and monitor models in production environments, ensuring performance and reliability.
• Communicate progress, challenges, and results effectively to both technical and non-technical stakeholders.

Requirements

• Strong programming skills in Python and experience with modern ML frameworks such as PyTorch or TensorFlow.
• Solid understanding of data preprocessing, model training, evaluation, and deployment.
• Familiarity with SQL and general data manipulation workflows (ETL, data cleaning, etc.).
• Ability to learn quickly, follow direction, and improve existing solutions.
• Excellent communication skills in English, both written and spoken.
• Ability to work both independently and collaboratively in a distributed, global team.

Preferred Qualifications

• 1–3 years of experience in data science, applied ML, or AI research.
• Exposure to AWS, Azure, or similar cloud platforms.
• Previous experience integrating ML models into production pipelines.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related fields.
• Based in South America or within a compatible time zone to collaborate effectively with U.S. and India-based teammates.