Machine Learning Engineer - Artificial Intelligence (2-5 yrs)

Position Summary :

We are seeking a Machine Learning Engineer with a robust understanding of ML principles and a proven track record of deploying models to production. Your work will be critical in enhancing our capabilities and accelerating our project timelines.

This position offers the chance to work on a wide array of projects, from foundational model development to the direct application of AI in identifying novel therapeutic opportunities.

Key Responsibilities :

- Implement and integrate open-source ML and non-ML repositories with our drug discovery platform.

- Design, develop, and deploy machine learning algorithms tailored to specific challenges of drug discovery.

- Collaborate with cross-functional teams, including bioinformaticians, chemists, and software engineers, to identify requirements and translate these into robust AI solutions.

- Continuously learn and adapt to new technologies and techniques in AI and machine learning to drive innovation within the team.

- Contribute to the maintenance and improvement of the machine learning infrastructure, ensuring best practices in code quality, testing, and deployment.

Qualifications :

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Computational Biology, or a related field.

- 2+years of experience in machine learning, with a strong portfolio of projects demonstrating experience with model deployment in production environments.

- Proficiency in Python and familiarity with deep learning libraries and frameworks such as PyTorch and TensorFlow (experience with RDKit is a plus, but not required).

- Experience working with cloud computing services (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes) is highly desirable.

- Strong problem-solving skills and the ability to work independently on complex projects.

- Excellent communication skills and the ability to work as part of a multidisciplinary team.

- A genuine curiosity and willingness to learn new technologies and approaches in the field of AI and drug discovery.