Iambic Therapeutics

Security Engineer

• Drive and mature the company-wide information security program and strategy including managing policies, standards, risk assessments, and the enterprise risk register
• Act as the primary internal authority on information security operations, advising leadership and department heads on risk and priorities
• Develop security metrics and reporting for technical and executive stakeholders
• Serve as a working technical mentor to security analysts, providing hands-on guidance, knowledge sharing, and day-to-day direction across IT and cloud security domains
• Own ISO 27001 certification and maintenance, including audits, evidence collection, and improvement
• Directly manage controls rationalization across frameworks (ISO 27001, SOC 2, NIST CSF, SOX ITGC) to support evolving compliance requirements
• Lead and execute the vendor and third-party risk management program
• Establish and maintain information security controls in alignment with life sciences regulatory requirements, including 21 CFR Part 11 and GxP
• Partner with the Software, cloud security, and DevOps teams on expanding industry-standard security practices into the software development lifecycle
• Actively participate in security operations across the corporate IT environment, including hands-on involvement in endpoint security, identity and access management, vulnerability management, and security monitoring
• Define cloud security governance standards and policies for SaaS-hosted environments and oversee compliance
• Own and continuously improve the company-wide security awareness and training program
• Champion a realistic, risk-based security culture across a diverse workforce spanning research, clinical, and corporate functions

Associate Director, Information Security

Machine Learning Engineer

• Research and implement architectural improvements to large-scale multimodal transformer models for biomedical applications
• Investigate hybrid modeling approaches that combine learned representations with domain-informed structure or inductive biases
• Optimize training pipelines for efficiency, stability, and scalability across many-GPU clusters
• Develop and apply inference optimization techniques to support deployment in interactive discovery workflows
• Design and maintain benchmarking and evaluation frameworks that track model quality across modalities and downstream tasks
• Collaborate with ML and software engineering colleagues to deploy and operationalize models
• Partner with computational chemists, medicinal chemists, and biologists to ensure model development is grounded in drug discovery needs
• Communicate results to internal teams, external partners, and at conferences
• Write high-quality research and engineering code: refactor, test, document, and package ML components to support team velocity
• Mentor interns and junior team members through technical guidance, code reviews, and best practices in ML experimentation
• Contribute to the strategic research roadmap for Enchant and related multimodal technologies

Machine Learning Scientist – Large Multimodal Models

Data Engineer

• Design, build, and maintain agentic systems for automated data acquisition from public and proprietary biomedical data sources
• Develop LLM-based pipelines for data cleaning, normalization, and formatting across diverse data modalities (e.g., molecular, genomic, clinical, literature)
• Implement automated quality-control workflows that detect anomalies, flag inconsistencies, and enforce data standards
• Evaluate and iterate on agent architectures, prompting strategies, and tool-use patterns to improve reliability and throughput
• Collaborate with ML scientists on the Enchant team to understand data requirements and translate them into scalable acquisition and processing systems
• Monitor and maintain data pipelines in production, diagnosing failures and improving robustness over time
• Document data provenance, processing decisions, and quality metrics to support reproducibility and auditing

Machine Learning Scientist – Agentic Data Pipelines

• Work embedded with ML scientists to co-develop and refine model training and evaluation workflows
• Translate experimental research code into maintainable, well-structured, and reusable systems
• Build and expand benchmarking systems for running models on structural and affinity datasets, computing metrics, and supporting reproducible evaluation
• Enable rapid iteration by developing tooling and interfaces that expose new capabilities to researchers
• Contribute to the ongoing development and productization of NeuralPLexer
• Collaborate with platform and infrastructure engineers on scaling workflows where needed, without owning core infrastructure
• Perform code reviews and actively mentor best practices in software engineering across the team
• Improve reliability, clarity, and reproducibility of ML workflows and supporting systems
• Communicate technical work effectively across a cross-functional research and engineering team

Software Engineer II – Machine Learning Systems, Productization

Clinical Operations

• Provide end-to-end operational leadership for complex clinical trials from start-up through close-out, ensuring delivery on time, within budget, and in compliance with global regulations and company SOPs
• Lead cross-functional study teams and drive alignment across Clinical Development, Regulatory, Biometrics, and external partners
• Develop and execute enrollment, site management, and monitoring strategies to ensure high-quality trial conduct and performance
• Oversee CRO and vendor performance, including KPI management, monitoring quality oversight, document review and approval, and vendor selection support
• Partner with Data Management and Medical to conduct ongoing data review and ensure timely query resolution
• Develop and manage key study documents and operational tools, including protocols, informed consent forms, project plans, budgets, and study materials.
• Lead study-related training for investigators, site personnel, and internal teams.
• Proactively identify, assess, and escalate operational risks with mitigation strategies and clear recommendations.
• Mentor and support junior clinical operations staff, including potential dotted-line management responsibilities.
• Travel up to 10% as required to support study oversight and site engagement

Iambic Therapeutics

Associate Director, Information Security

Machine Learning Scientist – Large Multimodal Models

Machine Learning Scientist – Agentic Data Pipelines

Software Engineer II – Machine Learning Systems, Productization

Senior Clinical Trial Manager, Clinical Operations

Software Engineer II, Machine Learning Systems – Productization