Machine Learning Engineer (Python) – Remote

About the role

We are looking for a Machine Learning Engineer specialized in Python to design, train, and deploy ML models in production. The role focuses on building scalable pipelines and delivering business value through high‑performance AI solutions. You will work remotely with a global team of top‑tier engineers.

Key responsibilities

• Design and implement production‑ready ML models and algorithms using Python.
• Build and optimize end‑to‑end ML pipelines, including data preprocessing, feature engineering, and model training.
• Deploy models at scale with frameworks such as PyTorch and TensorFlow in production environments.
• Manage and transform large datasets on platforms like Databricks, ensuring data quality and reliability.
• Monitor model performance in production and implement retraining strategies to address data drift.
• Collaborate with cross‑functional teams to align model architecture with business goals and infrastructure requirements.

Required profile

• Minimum 4 years of experience in Machine Learning Engineering, Data Science, or Software Engineering.
• Proven track record of designing, training, and deploying ML models in production.
• Advanced proficiency in Python and deep‑learning frameworks such as PyTorch or TensorFlow.
• Hands‑on experience with Databricks for managing and scaling ML workloads.
• Strong background in optimizing model performance and ensuring system scalability.
• Advanced proficiency in English.

Required skills

• Python
• PyTorch
• TensorFlow
• Databricks
• Machine Learning model design, training and deployment
• Data preprocessing and feature engineering
• Large‑scale dataset management
• Model monitoring and retraining

What we offer

• 100 % remote work from anywhere.
• Competitive compensation paid in USD or local currency.
• Provided hardware and software setup for home office.
• Flexible schedule – create your own working hours.
• Paid parental leave, vacation and holidays.
• Multicultural environment collaborating with the world’s top 1 % tech talent.
• Mentorship, career development and growth opportunities.