Flagship Labs 104 (FL104) is a privately held, early-stage company leveraging artificial intelligence and large language models (LLMs) to transform how we reason about complex phenomena. This is a unique opportunity to be at the forefront of scientific innovation, as we leverage cutting-edge advancements in AI and ML to drive breakthroughs in drug discovery and fundamental science.

About Flagship

Flagship Pioneering is a biotechnology company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

Position Summary:

We're looking to welcome a dynamic Senior MLOps Engineer to our scientific team. The successful candidate will play a pivotal role in the design, development, and application of LLM-based software to support scientific reasoning. It's a unique opportunity to influence our team’s culture and tackle intricate technical challenges in an innovation-driven environment. This role is among the first hires, and we’re looking for someone who is excited to help drive the technical and scientific direction of the company.

Key responsibilities:

• Lead the design, implementation, and optimization of end-to-end MLOps pipelines for deploying LLMs and agentic frameworks into production environments.
• Develop approaches for automated optimization of LLM agent systems using techniques such as reinforcement learning and autoML.
• Collaborate with scientists and engineers to conduct experiments to optimize and assess LLM performance, including running evaluations and synthesizing key findings.
• Establish and manage observability practices using tools like MLflow, including logging for traceability and alerting for anomaly detection and performance monitoring.
• Streamline model deployment with CI/CD pipelines using GitLab or Jenkins, integrating APIs and following software engineering best practices.
• Drive infrastructure improvements and advocate for rigorous testing frameworks to ensure robust system performance.

Qualifications:

• Bachelor’s in computer science or a related field and 5+ years of industry experience or M.S. and 3+ years of experience
• Demonstrated experience in designing, building, and maintaining production-level AI and ML pipelines.
• Proficiency in Python and exposure to other major programming languages.
• Extensive experience with AWS services, including EC2, ECS, S3, Lambda, and RDS, while adhering to well-architected best practices.
• Proficiency in workflow orchestration tools like Kubernetes or Metaflow and containerization.
• Proficiency in observability tools like MLflow or Langfuse for model monitoring and management.
• Demonstrated ability to establish rigorous testing frameworks and enforce high code quality standards.
• Energetic self-starter with the ability to work effectively in a startup environment.

Preferred Qualifications:

• Experience in designing and implementing LLM agent systems.
• Experience with Reinforcement Learning (RL) or autoML.
• Software development experience in the pharmaceutical or biotech industry is a distinct advantage.

Why Join Us?

FL104 offers you a unique opportunity to:

• Collaborate with highly talented, interdisciplinary team members.
• Participate in the evolution of a pioneering early-stage company, with the immense potential to transform how much a single scientist can accomplish.
• Contribute to a proactive work culture, with an emphasis on mutual learning and continuous improvement.
• Engage with the broader Flagship community comprising thousands of scientists through ecosystem-wide seminars and events.