Contract, AI Engineer

South San Francisco, California, United States

Cytokinetics

Cytokinetics is committed to developing potential medicines for people with diseases of impaired muscle function. Learn more about our medicines and research.

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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 (LLMs) and integrate with current state of the art solutions.
  • Experience with cloud platforms such as Microsoft Azure or AWS.
  • Hands-on experience with cloud data engineering tools.
  • Knowledge of Cloud Composer for orchestrating data workflows.
  • Knowledge of GCP requirements and pharmaceutical related regulations
  • Excellent problem-solving skills and attention to detail.
  • Ability to work effectively in a fast-paced and dynamic environment.

If you are passionate about leveraging Gen-AI in cloud to build robust and efficient data solutions for clinical development, and you meet the above qualifications, we encourage you to apply for this exciting opportunity.

Actual salary at the time of hire may vary and may be above or below the range based on various factors, including, but not limited to, the candidate’s relevant qualifications, skills, and experience, as well as the service line and location where this position may be filled.

Salary Pay Range$85—$120 USD

Our employees come from different backgrounds, and we celebrate those differences. We are looking for the best candidates for our open roles, but do not expect applicants to meet every qualification in order to be considered. If you are excited about what you could accomplish at Cytokinetics and believe you can add value to our team, we would love to hear from you.

Please review our General Data Protection Regulation (GDPR) policy PRIOR to applying.  

Our passion is anchored in robust scientific thinking, grounded in integrity and critical thinking. We keep the patient front and center in all we do – all actions and decisions are in service of the patient and their caregivers. We champion integrity, ethics, doing the right thing, and being our best selves.

Fraud Warning: How to Identify Impersonated Cytokinetics Job Postings and Offers

Recently, there have been fraudulent employment offers being sent to candidates on behalf of Cytokinetics. Please be advised that all legitimate offers from Cytokinetics will come directly from our official email domain (Cytokinetics.com) and will only be made after completing a formal interview process.

Here are some ways to check for authenticity:

  • We do not conduct job interviews through non-standard text messaging applications
  • We will never request personal information such as banking details until after an official offer has been accepted and verified
  • We will never request that you purchase equipment or other items when interviewing or hiring
  • If you are unsure about the authenticity of an offer, or if you receive any suspicious communication, please contact us directly at talentacquisition@cytokinetics.com

Please visit our website at: www.cytokinetics.com

Cytokinetics is an Equal Opportunity Employer

 

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Anaconda APIs AWS Azure Banking Biology Claude Computer Science Docker Engineering GCP Git GPT GPT-4 LLMs Machine Learning ML models Model deployment NoSQL Pharma Python PyTorch Security SQL TensorFlow Testing

Region: North America
Country: United States

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