Artificial Intelligence Engineer - Bioinformatics

Role Summary:

We are looking for a skilled Artificial Intelligence Engineer to develop sophisticated AI systems and applications in biological and drug manufacturing. Responsibilities include designing and developing artificial intelligence models for both biological therapeutics and GMP automation (robotics), assessing biotherapeutics manufacturing problems to propose effective AI solutions, and enhancing the performance of existing AI systems. You will work in a cross-functional team of cloud engineers, biological scientists, manufacturing engineers, data bioinformatics analysts, and 3P cloud services engineers and solutions architects.

Responsibilities:

• Design and develop AI models and applications for biological prediction models and manufacturing robotics.
• Translate our customers’ problems into AI solutions.
• Translate our manufacturing continuous improvement needs into AI solutions.
• Work with both internal and external data scientists to transform data science prototypes into high-performance production applications.
• Implement algorithms to enhance the performance of AI systems.
• Keep abreast of developments in AI and propose and implement new innovative solutions.
• Collaborate with stakeholders to identify opportunities for leveraging company data to drive business solutions.
• Maintain and optimize AI systems for performance.
• Ensure AI systems align with organizational goals.

Qualifications:

• Proven experience as an AI Engineer or similar role.
• Understanding of machine learning, deep learning, data mining, and algorithms.
• Proficiency in programming languages like Python, Java, and R.
• Familiarity with AI frameworks (like TensorFlow or PyTorch) and libraries.
• Strong math skills (e.g., statistics, algebra).
• Experience with cloud platforms (e.g., AWS, OCI, or GCP).
• BSc degree in Computer Science, Engineering or a related field.

Desired Characteristics:

• Ability to ideate, test using Proof-of-Concept principles, validate, and ongoing verification for AI protocols/designs.
• Ability to map cloud AI processes, including the understanding of hybrid environments.
• Ability to optimize the AI environment for better performance and also developing APIs to help other applications access the AI system.
• Analyze complex distributed system challenges to drive design decisions targeted toward reliability, availability, scalability, and resiliency.
• Experience with Disaster Recovery and Migration is a plus.
• Analytical: Strong analytical skills with a keen eye for detail and accuracy.
• Innovative: Continuously seeks innovative ways to leverage data and AI to solve complex problems.
• Collaborative: Works well in cross-functional teams and values diverse perspectives.
• Adaptable: Able to adapt to new technologies and methodologies quickly.