Senior AI Research Engineer (AI)

Location: Hybrid role based within commuting distance of a hirify.global location in the United States, with on-site work an average of 2.5 days per week. Locations include Bothell, Washington; San Diego, California; Cambridge, Massachusetts; Groton, Connecticut; Pearl River, New York; and New York City, New York.

Annual base salary: $106,000–$176,600, plus eligibility for a 15% bonus target and share-based long-term incentive program.

Company

hirify.global is building AI capabilities for drug discovery and scientific research across its R&D organization.

What you will do

• Design, develop, and deploy production-grade AI systems for multimodal biomedical models and intelligent agents.
• Build data pipelines, retrieval systems, evaluation frameworks, knowledge systems, inference services, and human-in-the-loop workflows.
• Own architecture, implementation, testing, deployment, monitoring, operational support, and continuous improvement for an end-to-end subsystem or platform capability.
• Translate scientific and business needs into scalable, reliable, secure, and maintainable technical solutions.
• Partner with AI scientists, computational biologists, data engineers, and platform teams to turn research prototypes into reusable production systems.
• Contribute to architecture and code reviews, engineering standards, troubleshooting, technical coaching, and measurable improvements in performance, reliability, usability, and scientific impact.

Requirements

• PhD in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a related technical discipline with demonstrated software, systems, or machine learning experience; or a master's degree with 2+ years of relevant experience; or a bachelor's degree with 4+ years of relevant experience.
• Demonstrated experience designing and delivering production software or machine learning systems and owning solutions from architecture through deployment.
• Experience building reliable systems in cloud, distributed computing, or HPC environments, with maintainable, testable, and scalable software.
• Strong proficiency in Python, PyTorch or JAX, software architecture, system design, APIs, testing, debugging, version control, technical documentation, containers, orchestration, CI/CD, and deployment workflows.
• Depth in one or more of distributed GPU training, model serving and inference optimization, AI platforms and MLOps, data and knowledge systems, LLM and agentic architectures, retrieval systems and RAG, AI evaluation frameworks, or performance and infrastructure optimization.
• Ability to work across interdisciplinary teams, navigate ambiguity, solve complex problems, communicate technical concepts to broad audiences, influence decisions, and support less-experienced engineers.
• Candidates must be authorized to be employed in the United States by any employer and have permanent U.S. work authorization.

Nice to have

• Experience in life sciences, healthcare, biotechnology, or highly regulated industries.
• Experience with multimodal AI, scientific machine learning, computational biology, or cheminformatics.
• Experience implementing responsible AI practices, evaluation frameworks, and governance controls.
• Evidence of technical impact through deployed systems, publications, patents, open-source contributions, or reusable engineering platforms.

Culture & Benefits

• Meaningful ownership, technically ambitious challenges, collaboration with AI, engineering, computational biology, and drug discovery experts, and opportunities for growth.
• Benefits include a 401(k) with matching and an additional retirement savings contribution, paid vacation, holidays and personal days, caregiver/parental and medical leave, and medical, prescription, dental, and vision coverage.
• Relocation assistance may be available based on business needs and eligibility.
• U.S. work visa sponsorship, including TN, O-1, and H-1B, is not available now or in the future.