JOB DESCRIPTION

We are seeking a skilled Python Developer to join our team, working with machine learning to build innovative solutions. This role is ideal for someone with a passion for developing advanced systems and applying machine learning techniques to complex, data-driven challenges. As part of our team, you will work on cutting-edge projects that require the application of the latest research in machine learning and deep learning.

REQUIRED QUALIFICATIONS

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• At least 3 years of professional experience in Python development.
• Proficient understanding of machine learning fundamentals and data-driven model development.
• Experience in implementing machine learning systems and putting models into production.
• Familiarity with various machine learning architectures such as convolutional networks, autoencoders, and transformers.
• Experience using cloud platforms (AWS or GCP) for deploying machine learning models.
• Strong communication skills and the ability to work both independently and in a team setting.

PREFERRED QUALIFICATIONS

• Master’s or PhD in Machine Learning, Data Science, or a related field.
• Extensive experience working with high-throughput data environments and data lakes.
• Advanced knowledge of machine learning frameworks, particularly PyTorch or TensorFlow.
• Publications in machine learning or AI journals or conferences.
• Experience with advanced techniques such as generative adversarial networks (GANs) or time-series applications.

• Design and implement Python-based systems for machine learning applications.
• Develop and optimize machine learning workflows, including dataset creation, data exploration, and data wrangling.
• Create and refine training pipelines and preprocessing modules for faster experimentation.
• Implement and train machine learning models using techniques like unsupervised learning, convolutional networks, and transformers.
• Work on integrating machine learning models into production environments using cloud platforms such as AWS or GCP.
• Collaborate closely with engineers to ensure the deployment of models into scalable, production-grade systems.
• Communicate complex technical details and progress to non-technical stakeholders.