Contract, AI Engineer

Cytokinetics is a late-stage, specialty cardiovascular biopharmaceutical company focused on discovering, developing and commercializing first-in-class muscle activators and next-in-class muscle inhibitors as potential treatments for debilitating diseases in which cardiac muscle performance is compromised. As a leader in muscle biology and the mechanics of muscle performance, the company is developing small molecule drug candidates specifically engineered to impact myocardial muscle function and contractility.

We are seeking a skilled AI/Machine Learning Engineer with backend experience to join our dynamic team. The position will report to the Director of Clinical Systems.  The ideal candidate will have a strong background in building out machine learning solutions and is comfortable with AWS and/or Azure. Experience with cloud computing knowledge will be a significant advantage. The candidate will be responsible for designing, developing, and maintaining scalable gen-AI applications that advance our AI clinical development solutions.  Your work will encompass designing, developing, and optimizing interfaces with large language models (LLMs) to integrate them into our evolving AI initiatives. You will experiment, innovate, and collaborate across teams, laying the foundation for our future AI projects. Your goal is to create seamless interactions with LLMs, ensuring security, efficiency, and alignment with our company's mission and values.  Cytokinetics is stepping into an exciting new phase, initiating several AI projects with LLMs. Be a part of this transformative journey and help us explore the limitless possibilities of AI.

Responsibilities:

• Collaborate with Teams: Engage in meetings with diverse stakeholders to understand workflows and provide insights. Educate teams on the potential and boundaries of integrating LLMs into existing systems.
• Craft LLM Prompts: Creatively design the prompts necessary to guide LLMs towards specific tasks, ensuring alignment with desired outcomes.
• Develop Integration Software: Construct robust software to process LLM responses and enable integration with existing applications.
• Implement Intelligent Constraints: Design constraints to prevent users from asking questions that LLMs cannot answer, maintaining alignment with the task objectives.
• Assess and Mitigate Security Risks: Monitor and evaluate potential security risks like prompt injection or sensitive data leakage, implementing necessary security protocols.
• Coordinate Complex AI Tasks: Design agents to manage intricate tasks such as multi-database SQL queries or automated workflows.
• Experiment and Innovate: Lead experiments to test LLM communications, analyzing responses to ensure desired results, and iteratively refine processes.
• Participate in Design Meetings, Standups, and Planning Sessions: Engage in the necessary meetings to develop and deliver solutions within the team.
• Develop and maintain backend services using Python, focusing on AI-driven applications on cloud platforms.
• Optimize database performance and manage complex data structures for AI models.
• Design and implement APIs for seamless integration with AI models and applications.
• Collaborate with data/AI professionals to integrate machine learning models into production systems.
• Ensure the security and compliance of clinical trial data, adhering to GCP requirements and other regulations.
• Collaborating with clinical systems specialists, data scientists, and other stakeholders to understand data requirements and build appropriate solutions for clinical development.
• Participate in code reviews, testing, and quality assurance processes.
• Diagnose and resolve issues related to AI model deployment and backend infrastructure.
• Document development processes, system designs, and architectural decisions.

Requirements:

• Bachelor's degree in Computer Science, Engineering, or related field
• 1-3 years’ experience with large language models like Claude, GPT-4 ideally in an industry setting 
• Proficiency in Python and modern development environments including Git, Anaconda, PiP, Docker, and Cloud services
• Ability to develop production-ready standalone libraries beyond notebook code.
• Individual contributor mindset, with strong problem-solving and communication skills
• Demonstrable previous work with LLM interfaces, sharing code repositories if applicable during the interview process.
• Proven experience in development using Python, AI and machine learning tools such as PyTorch and TensorFlow. Knowledge in clinical development is a plus.
• Strong understanding of database management, including SQL and NoSQL databases.
• Able to train and fine-tune AI models