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.
Key Responsibilities
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.
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.