Machine Learning Engineer – 5 to 8 years
Role Summary:
We are seeking a Machine Learning Engineer (MLE) who will play a critical role in developing and implementing machine learning & deep learning solutions that drive innovation and efficiency across our projects. The ideal candidate will possess a strong foundation in machine learning, deep 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 & deep 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 & deep 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, regression, outlier analysis) to solve complex problems.
- Apply deep learning techniques (e.g., Deep Neural Networks, Computer Vision, NLP, Transformers etc) to solve complex problems.
- Present solutions to stakeholders clearly and concisely.
Basic Qualifications:
- Proficiency in Python and knowledge of key machine learning & deep learning packages such as numpy, pandas, scikit-learn, xgboost, pytorch, tensorflow etc.
- Understanding of data structures, data modeling, software architecture, and software development tools, including Git and virtual environments.
- Demonstrated ability to apply machine learning & deep learning techniques to solve real-world problems.
- Experience in deploying machine learning & deep 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 machine learning & 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 & deep learning. The successful candidate will contribute to a range of exciting projects, leveraging machine leaning & deep learning to make significant impacts in our operations and research endeavors.
