AI Research Engineer
About The Position
We are seeking a Research Engineer to join our interdisciplinary AI team, working at the intersection of machine learning and therapeutic discovery. In this role, you will collaborate closely with AI scientists, engineers, and drug discovery experts to design, build, and deploy AI systems that accelerate the identification and development of novel therapeutics. This role spans a range of problem spaces, from building production-grade machine learning systems for biological data to developing next-generation AI agents that can reason over complex biomedical information. Depending on your background and interests, you may focus on applied ML systems, agentic AI, or a combination of both. We are particularly interested in candidates who are excited to translate cutting-edge advances in AI into real-world impact within drug discovery, and who are comfortable working in fast-paced, cross-functional environments.
Requirements
- Degree in Computer Science, Machine Learning, Computational Biology, or a related field.
- Strong programming skills in Python and experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow).
- Solid understanding of machine learning and deep learning fundamentals.
- Experience working with complex datasets and building end-to-end ML workflows.
- Experience with large-scale model training or foundation models.
- Experience working with biological or biomedical datasets (e.g., genomics, transcriptomics, clinical data).
- Familiarity with LLMs, agent-based systems, or complex orchestration frameworks.
- Strong problem-solving skills and ability to work in a collaborative, multidisciplinary environment.
Nice To Haves
- 5+ years of industry experience building and deploying ML systems in production environments
- Proven track record of scaling models and delivering impactful, production-grade solutions.
- Experience leading technical projects and driving cross-functional execution.
- Strong academic or early industry experience, particularly in areas such as LLMs, agentic systems, or computational biology.
- Hands-on experience with model development, experimentation, or applied ML projects.
- Demonstrated ability to learn quickly and apply new techniques to real-world problems.
- Publication record at top ML conferences (NeurIPS, ICML, ICLR) or equivalent industry impact.
Responsibilities
- Design and develop AI/ML systems to support therapeutic discovery, including model training, evaluation, and deployment.
- Build scalable pipelines for processing and integrating large, complex biological datasets.
- Collaborate with computational and experimental teams to define problems, evaluate outputs, and iterate on solutions.
- Develop robust, production-ready systems that can be integrated into scientific workflows.
- Explore and apply emerging AI techniques to improve model performance and system capabilities.
- Build agentic AI systems capable of multi-step reasoning, planning, and tool use in biomedical contexts.
- Develop LLM-based systems that retrieve, synthesize, and reason over scientific literature, omics data, and clinical datasets.
- Integrate external tools (analysis pipelines, simulation engines, databases) into intelligent, autonomous workflows.
- Design systems that combine structured and unstructured data in scalable, production environments.
Benefits
- We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers.
- A Summary of Benefits is available for all applicants.
- We offer a competitive package that includes base salary, bonus, and equity.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
