Senior Machine Learning Engineer

We are seeking an experienced Machine Learning engineer with 3 to 5 years of professional experience to join us on a project focused on enhancing and extending a specific system within our platform. This role is suited for someone who can quickly adapt to an established architecture and contribute effectively to delivering high-quality, production-ready software. The emphasis is on hands-on development, technical documentation, aligned with current technical direction, not long-term design ownership or system re-architecture.

The Machine Learning team is responsible for developing and maintaining machine learning models. We are collaborative, action-oriented and passionate advocates of using ML/AI to solve customer problems. Our team operates with transparency and alignment, guided by scaled agile practices that promote continuous improvement.

We’re driven by values that shape how we work together every day:
Teamwork, ownership, accountability, proactivity, transparency, empathy, inclusivity, and a commitment to continuous learning and growth.


Job Description

• Solid experience in machine learning algorithms, including linear regression, SVM, decision trees, neural networks, and clustering, along with familiarity with best practices in the field.
• Solid experience in deep learning required especially training Natural Language Processing Models
• Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, Transformers, or scikit-learn.
• Practical experience working with and utilizing large language models (LLMs) and other GenAI technologies.
• Demonstrated ability to build and deploy ML models, design training pipelines, and support ML applications in production environments.
• Competent in building ML Pipelines using AWS services such as Bedrock and Sagemaker pipeline and model endpoints.
• Proficiency in SQL
• Fluent in English
   

Job Responsibilities

• Responsible for developing and maintaining machine learning models.
• Write clear, concise technical documentation to support ongoing maintenance and knowledge transfer.
• Actively participate in code reviews to maintain code quality and ensure adherence to established patterns.
• Quickly understand and navigate an existing codebase and system architecture, providing solutions aligned with current technical direction.
• Troubleshoot and resolve issues across the full stack of the assigned system.