Senior Software Engineer - AI Research

2 days ago

🏡 Remote – New York

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Formation Bio

Bringing new treatments to patients faster and more efficiently.

51 - 200

Description

• Lead the design, development, and deployment of software solutions that build innovative AI tools and models in the strategic drug development process. • Collaborate with cross-functional teams, including product managers and domain experts, to discover, build, and iterate on innovative features and products. • Ensure the scalability, security, and performance of our software systems. • Rapidly develop and iterate on proofs-of-concept to test new ideas and hypotheses to efficiently validate and evolve our software solutions in alignment with strategic objectives in drug development. • Stay abreast of emerging trends and advancements in AI, LLMs, and software development to continually enhance our product offerings. • Act as an internal evangelist for use of AI and LLMs, providing expert guidance and insights to other teams within the organization.

Requirements

• Master’s degree or higher in Computer Science, Engineering, AI, or Machine Learning or a related field, or equivalent experience. • Minimum of 7 years of experience in software development, with a demonstrated ability to thrive in ambiguous and rapidly-changing environments, with a proven track record of contributing significantly to the successful launch and scaling of new and innovative products, especially in a 0-1 setting. • Experience with AI and machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Langchain, llamaindex, RAGAs). • Exceptional collaboration and communication skills to effectively engage and work along stakeholders from diverse disciplines and varying levels of technical expertise. Ideally, adept at translating complex technical concepts into clear, actionable insights for all audiences. • Hands on experience with AI technologies, particularly in LLMs and machine learning. • Familiarity with cloud infrastructure (e.g., AWS, Azure, GCP) and the full end-to-end process of modern software deployment (e.g., containerization, CI/CD). • Experience in the pharmaceutical or biotech industry is a plus, but not required

Benefits

• Competitive compensation • Equity • Generous perks • Location flexibility • Comprehensive benefits

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