Remote Machine Learning Engineer

About the Role

We are seeking a talented Remote Machine Learning Engineer to join a global tech company and help build, deploy, and scale intelligent systems that power next-generation products. In this role, you will work across the full ML lifecycle — from data exploration and model development to production deployment and monitoring — collaborating with cross-functional teams of engineers, data scientists, and product managers.

You will design and implement machine learning pipelines, experiment with novel architectures, and optimize models for performance and scalability in production environments. The position is fully remote, offering flexibility to work from anywhere while contributing to impactful, data-driven solutions used by customers worldwide.

Responsibilities

• Develop, train, and evaluate machine learning models for real-world applications.
• Build and maintain scalable data pipelines and feature stores.
• Deploy models to production using MLOps best practices (CI/CD, monitoring, versioning).
• Collaborate with engineering and product teams to translate business problems into ML solutions.
• Conduct experiments, analyze results, and communicate findings to stakeholders.
• Stay current with advances in ML research and apply them to practical problems.

Why Join

Work with a distributed, international team on challenging problems at scale, with strong emphasis on engineering excellence, autonomy, and continuous learning.

• Bachelor's or Master's degree in Computer Science, Machine Learning, or related field.
• 3+ years of experience building and deploying ML models in production.
• Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, or scikit-learn).
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
• Familiarity with MLOps tools and practices (MLflow, Kubeflow, Airflow).
• Solid understanding of statistics, algorithms, and data structures.
• Excellent communication skills and ability to work independently in a remote setting.
• (Nice to have) Experience with LLMs, RAG systems, or generative AI.