Forward Deployed ML Engineers (AI Infrastructure)

Location: Stockholm; in-person work required

Company

hirify.global is building an infrastructure platform for AI workloads, including model serving, training, audio pipelines, and scientific computing.

What you will do

• Architect and optimize production AI workloads on hirify.global for leading AI companies and foundation model labs.
• Work on LLM serving, model training, audio pipelines, scientific computing, and other demanding workloads.
• Conduct technical demos, experiments, and proofs of concept that demonstrate hirify.global's performance.
• Contribute to open-source projects such as SGLang and publish technical content across the AI stack.
• Collaborate with product and sales teams as both an engineer and a product stakeholder.
• Build trusted relationships with CTOs, engineering leaders, and ML leads.

Requirements

• 2+ years of professional ML engineering experience.
• Hands-on experience in at least one area such as inference optimization, model training, GPU programming, or ML infrastructure.
• Familiarity with serving toolchains such as vLLM or SGLang and training toolchains such as slime, verl, or TRL.
• Strong communication skills for discussing technical architecture and tradeoffs with engineering teams and technical leadership.
• Interest in working directly with customers to understand and solve complex technical problems.
• Willingness to work in person in Stockholm.

Nice to have

• Side projects, open-source contributions, or published work in ML or systems performance.

Culture & Benefits

• Work with companies including Suno, Lovable, Cognition, and Meta.
• Collaborate with software engineers, computational scientists, ML engineers, former founders, researchers, and experienced engineering leaders.
• Contribute to open-source projects and technical publications.
• Work at the intersection of deep technical engineering and direct customer impact.