Research Scientists and Engineers in Machine Learning and Artificial Intelligence (AI)

Location: San Francisco; work authorization in the U.S. is required.

Company

hirify.global is an AI research lab developing general biological intelligence, multimodal genome language models, and biosecurity and biodefense systems.

What you will do

• Design, evaluate, deploy, fine-tune, adapt, and architect frontier AI and multimodal genome language models for biological systems.
• Design and run machine learning experiments for biosecurity and biodefense applications across genomics, protein biology, and cellular systems.
• Translate technical capabilities into deployable early-warning platforms, sequence-screening tools, attribution technologies, and rapid detection and response pipelines.
• Design post-training pipelines, domain adaptation strategies, evaluation frameworks, benchmarks, and prediction and design approaches using foundation models.
• Analyze model behavior, run ablations, and investigate reasoning, failure modes, mechanistic interpretability, sequence characterization, and model understanding.
• Collaborate with computational biologists, AI scientists, systems architecture engineers, government organizations, and external partners to align systems with real-world workflows.

Requirements

• Strong technical background in deep learning for large-scale classification, retrieval, or generative models.
• Strong Python and machine learning tooling experience, including PyTorch or JAX, experiment management, and distributed training.
• Experience applying machine learning models to biological data and challenging prediction tasks.
• Ability to design evaluation tasks and benchmarks beyond simple accuracy metrics and connect computational outputs to actionable downstream applications.
• Familiarity with molecular biology and biological data modalities, particularly genomics, gene regulation, protein biology, or cellular systems, or strong interest in applying AI and machine learning in this space.
• Ability to reason concretely about the capabilities and limitations of biological AI systems, their real-world risks, and methods to measure and mitigate those risks.
• High agency, including defining problems, independently executing work, and shipping results.

Nice to have

• Familiarity with multimodal biological modeling, including genomics or protein structure.
• Experience building robust evaluation suites for large AI systems and scaling machine learning experiments across large GPU clusters.
• Research publications in machine learning for biology, chemistry, or related areas.
• Experience in applied biosecurity or biodefense, such as pathogen-agnostic detection or countermeasure development.
• Familiarity with bioinformatics algorithms and tools such as BLAST, DIAMOND, or HMMER.
• Experience with biological foundation models such as Evo, ESM, or AlphaFold.

Culture & Benefits

• Mission-driven work focused on biological intelligence, human health, biosecurity, and biodefense.
• Collaborative, rigorous, creative, and cross-disciplinary environment spanning AI labs, biotechnology companies, hospital systems, and national research institutes.
• Fast-moving and ambiguous environment with high ownership.
• Competitive compensation and comprehensive benefits.
• Support for continual learning.