Machine Learning Engineer

Job Description:

Designation: Machine Learning Engineer

Years of Experience : 8 to 14 Years

Location - Remote

Role Summary:

We are seeking a Machine Learning Engineer (MLE) contractor who will play a critical role in developing and implementing machine learning solutions that drive innovation and efficiency across our projects. The ideal candidate will possess a strong foundation in machine learning, data processing, and software development, with the ability to work seamlessly with existing models and deploy new models into production.

Key Responsibilities:

• Develop, optimize, and deploy machine learning models to support project objectives.
• Process and analyze large datasets to inform model development and enhancements.
• Maintain and improve existing machine learning models within our systems, ensuring they meet our standards for accuracy and performance.
• Collaborate with cross-functional teams to integrate machine learning solutions into our operational framework.
• Utilize software development tools to maintain a robust, scalable codebase.
• Apply a variety of machine learning techniques (e.g., statistics, clustering, classification, outlier analysis) to solve complex problems.

Basic Qualifications:

• Proficiency in Python and knowledge of key machine learning packages such as numpy, pandas, scikit-learn, and xgboost.
• Understanding of data structures, data modeling, software architecture, and software development tools, including Git and virtual environments.
• Demonstrated ability to apply machine learning techniques to solve real-world problems.
• Experience in deploying machine learning models in code and working with existing models.
• Strong problem-solving skills and the ability to work independently or as part of a team.

Preferred qualifications:

• Experience in building and accessing API endpoints.
• Cloud computing experience, particularly with AWS.
• Experience with deploying open source deep learning models, with a preference for those related to Life Sciences.
• Proficiency in Deep Learning frameworks, such as PyTorch.
• Experience in building and managing MLOps pipelines.

This role requires a blend of technical expertise, creativity, and a passion for innovation in machine learning. The successful candidate will contribute to a range of exciting projects, leveraging machine learning to make significant impacts in our operations and research endeavors.