ML Engineer (Generative AI)

TL;DR

ML Engineer (Generative AI): Designing, optimizing, and deploying robust LLM applications and agentic workflows for brands and startups with an accent on production-grade software engineering and NLP. Focus on building evaluation frameworks, integrating AI capabilities into serverless architectures, and translating business requirements into technical scopes.

Location: Remote (Must be based in Spain)

Company

hirify.global is a premier product design, engineering, and marketing firm specializing in custom AI, web, and mobile applications for established brands and funded startups.

What you will do

• Architect and implement generative AI solutions and classical ML models, balancing agentic architectures and deterministic pipelines.
• Design and maintain evaluation frameworks to measure AI quality, reliability, safety, and business impact.
• Integrate AI capabilities into web and mobile applications using serverless architecture (AWS Lambda) and API endpoints.
• Optimize prompts, system instructions, and chunking strategies to balance accuracy, latency, and cost.
• Process historical client data to train and fine-tune custom algorithms for forecasting and anomaly detection.
• Collaborate with stakeholders to translate ambiguous business requirements into viable technical prototypes and scopes.

Requirements

• 3+ years of experience in software engineering with a strong focus on machine learning and NLP.
• In-depth understanding of LLM architectures, context window mechanics, and semantic search techniques.
• Proven experience building and operating production AI systems, including monitoring and debugging.
• Exceptional Python coding skills and proficiency in SQL for data structuring and cleaning.
• Hands-on experience deploying ML or API services within the AWS cloud ecosystem.
• Fluent written and spoken English.

Culture & Benefits

• Annual paid vacation (20-25 days depending on tenure).
• Paid sick leave, 10 national holidays, and 2 company days off.
• Well-being budget and maternity/paternity leave.
• Up to 100% reimbursement for professional development courses and certifications.
• Hardware provided based on business needs.
• Strong positive engineering culture with a collaborative, remote-first environment.

Hiring process

• Initial short interview with HR.
• Technical interview with an ML Engineer and the CTO.
• Live-coding interview.