Lead Machine Learning Engineer (AI)

TL;DR

Lead Machine Learning Engineer (AI): lead the design, development, and deployment of scalable machine learning and AI systems for enterprise clients with an accent on machine learning, distributed systems, and production software engineering. Focus on guiding ML architecture decisions, mentoring engineers, and collaborating with cross-functional teams to deliver high-impact AI solutions.

Location: Fully Remote / European Residence required

Company

hirify.global (USA) is a dynamic team of software engineering specialists providing high-impact development services to Fortune 500 companies.

What you will do

• Lead design, development, and deployment of scalable ML and AI systems.
• Transform cutting-edge ML research into production-grade solutions.
• Guide ML architecture decisions and mentor engineering teams.
• Collaborate with cross-functional teams across multiple industries.
• Build scalable ML systems, data pipelines, and implement MLOps practices.

Requirements

• European Residence required.
• Strong written and spoken English communication skills.
• 8+ years in software engineering, machine learning engineering, or applied AI.
• 3+ years in technical leadership or mentoring teams.
• Experience deploying ML models in production with PyTorch, TensorFlow, or similar.
• Strong Python skills, backend/distributed systems, cloud platforms (AWS, Azure, GCP).
• Containerization (Docker, Kubernetes), MLOps, and model lifecycle management.
• Degree in Computer Science, Machine Learning, AI, or related field.

Nice to have

• Experience with LLMs, generative AI, or deep learning.
• Building ML platforms or internal AI tooling.
• Distributed training and large-scale data processing.
• Feature stores, model monitoring, ML observability.
• Client-facing consulting environments.

Culture & Benefits

• Competitive compensation with benefits, paid vacation, and sick leave.
• Work with globally diverse team on toughest engineering challenges.
• Ultra-flexible conditions: home office, desk at office/coworking, no travel.
• Startup environment with professional growth opportunities.
• Flexible hours focused on results, remote-first approach.