Job Description

Job Details About Formation Bio Formation Bio is a tech and AI driven pharma company differentiated by radically more efficient drug development. Advancements in AI and drug discovery are creating more candidate drugs than the industry can progress because of the high cost and time of clinical trials. Recognizing that this development bottleneck may ultimately limit the number of new medicines that can reach patients, Formation Bio, founded in 2016 as TrialSpark Inc., has built technology platforms, processes, and capabilities to accelerate all aspects of drug development and clinical trials. Formation Bio partners, acquires, or in-licenses drugs from pharma companies, research organizations, and biotechs to develop programs past clinical proof of concept and beyond, ultimately helping to bring new medicines to patients. The company is backed by investors across pharma and tech, including a16z, Sequoia, Sanofi, Thrive Capital, Sam Altman, John Doerr, Spark Capital, SV Angel Growth, and others. You can read more at the following links: Our Vision for AI in Pharma Our Current Drug Portfolio Our Technology & Platform At Formation Bio, our values are the driving force behind our mission to revolutionize the pharma industry. Every team and individual at the company shares these same values, and every team and individual plays a key part in our mission to bring new treatments to patients faster and more efficiently. About the Position We are looking for a Senior Software Engineer, Applied AI to join our dynamic team at Formation Bio. As we continue to revolutionize the drug development process, this role will center on the design, development, and deployment of advanced machine learning models, including those powered by large language models (LLMs) for classification, recommendation, and risk assessment. In this role, you'll apply cutting-edge machine learning techniques to real-world challenges in drug development, directly influencing decision-making and identifying new treatment opportunities. You will collaborate closely with data scientists, product managers, and domain experts in the pharmaceutical industry to develop reliable and scalable ML systems that drive strategic business decisions and improve clinical outcomes. If you are passionate about solving complex problems with AI and eager to make a tangible impact on patient outcomes, we'd love to meet you. Responsibilities Lead the design, development, and deployment of machine learning models for classification, recommendation, and risk assessment to enhance decision-making in drug development. Build and optimize predictive models, including classification, regression, time-series, and ranking algorithms, with a focus on robust deployment in production environments. Collaborate with cross-functional teams - including data scientists, engineers, and drug development stakeholders to design and deliver high-impact ML solutions. Work with large-scale proprietary datasets (e.g., SPOKE, Evaluate data, KOL transcripts), ensuring performance benchmarks are met within cloud-based infrastructure (AWS, GCP, Azure). Rapidly prototype and iterate on machine learning solutions, including proofs-of-concept, to explore innovative approaches and evaluate business impact. Integrate structured knowledge into ML pipelines using ontologies and document store architectures, enhancing model context and data retrieval. Design and build AI-driven listener agents that continuously ingest new information and trigger reanalysis of drug candidates using updated predictive models. Stay current with emerging trends in machine learning and generative AI, applying them to continuously evolve our modeling and decision-making capabilities. About You Master's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent experience. 6+ years of experience in software development and applied ML, with a focus on building predictive models, ranking systems, and risk assessment pipelines. Proven track record of designing, deploying, and maintaining ML and LLM models in production environments, including experience with versioning, scaling, and monitoring. Demonstrated ability to drive measurable business impact with ML and LLM solutions - from defining success metrics to iterating based on real-world feedback. Strong foundation in supervised, unsupervised, and reinforcement learning, as well as LLM techniques such as prompt engineering, retrieval-augmented generation (RAG), and fine-tuning. Proficient in Python, with deep experience in libraries such as TensorFlow, PyTorch etc Experience working with large-scale data pipelines and deploying ML models in cloud environments (AWS, GCP, or Azure). Familiarity with model evaluation techniques, including cross-validation, A/B testing, and confidence-based ranking. Experience building multi-agent AI systems, including listener/orchestrator agents for dynamic data ingestion and decision-making. Excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders and align teams around complex solutions. Experience in the pharmaceutical or biotech industry is a plus, but not required. A passion for applied AI, with a deep curiosity about how ML and LLMs can transform real-world systems and outcomes. What You'll Do Engineer the Future: Lead the creation and deployment of ML and LLM systems that support smarter, faster drug development decisions. Collaborate to Innovate: Partner with cross-functional teams to build user-focused tools and models that drive real-world impact. Own the Challenge : Ensure ML systems are scalable, secure, and reliable designed to thrive in a data-intensive, cloud-first environment. Prototype Fearlessly : Develop and iterate on proof-of-concept models to test bold ideas and unlock new opportunities. Stay Ahead: Continuously apply the latest advances in AI and machine learning to evolve our product capabilities. Champion Change : Advocate for AI-driven transformation across the organization, helping teams adopt ML and LLM solutions with confidence. Formation Bio is prioritizing hiring in key hubs, primarily the New York City and Boston metro areas, with additional growth in the Research Triangle (NC) and San Francisco Bay Area. Please only apply if you reside in these locations or are willing to relocate. Compensation: The target salary range for this role is: $180,000 - $230,000. Salary ranges are informed by a number of factors including geographic location. The range provided includes base salary only. In addition to base salary, we offer equity, comprehensive benefits, generous perks, hybrid flexibility, and more. If this range doesn't match your expectations, please still apply because we may have something else for you. You will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. #LI-hybrid BioSpace, Inc.

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