Senior NLP Engineer - LLM Lifecycle & Agentic Systems

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior NLP Engineer based in Switzerland.

This role sits at the core of building next-generation AI systems that power large-scale social and conversational products used by millions of people worldwide. You will be responsible for designing and improving advanced language models that enable intelligent, engaging, and human-like interactions across AI-driven companions and chat systems. The environment is highly research-driven yet production-focused, combining cutting-edge NLP experimentation with real-world deployment at global scale. You will work closely with multidisciplinary teams spanning data, validation, and product to continuously refine model behavior and quality. The role offers the opportunity to influence the full LLM lifecycle—from training and fine-tuning to deployment and optimization. You will also contribute to shaping the organization’s NLP roadmap by tracking the latest advancements in AI research and open-source ecosystems. This is a fully remote position within a globally distributed, innovation-focused engineering culture.

Accountabilities

• Train, fine-tune, and optimize large language models powering AI companion and conversational systems at scale.
• Design, build, and maintain agentic frameworks, including agent harnesses, reasoning loops, and chat orchestration systems.
• Own the end-to-end LLM lifecycle, from data preparation and model training to deployment and production monitoring.
• Research and evaluate state-of-the-art NLP techniques and translate them into actionable improvements for the product roadmap.
• Implement and improve alignment methods such as RLHF, DPO, and other post-training optimization strategies.
• Collaborate with validation, content, and data teams to design experiments and measure model quality and performance.
• Contribute to scalable backend systems supporting high-throughput model inference and production AI workloads.
  
  

Requirements

• Strong hands-on experience training and fine-tuning large language models in production or research environments.

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• Proven experience building agentic pipelines, LLM orchestration systems, or AI agent frameworks.
• Deep understanding of transformer architectures, PyTorch, and modern NLP/ML libraries.
• Solid knowledge of alignment techniques such as RLHF, DPO, and related post-training methodologies.
• Background in backend or systems engineering using Python (preferred), Go, or C#, with exposure to scalable deployment architectures.
• Experience in AI-first companies or research-driven product teams (e.g., conversational AI, LLM startups) is highly desirable.
• Strong analytical thinking, experimentation mindset, and ability to translate research into production-ready systems.
• Nice to have: experience with multimodal models (text, image, video), distributed training on large datasets, or CV-related model development.
  
  

Benefits

• Fully remote work opportunity with global team flexibility
• 28 days of annual vacation plus 7 additional wellness days
• Performance bonuses, including referral rewards up to $5,000

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• Financial support for professional development (50% coverage of training, conferences, and industry events)
• English language learning discounts through corporate programs
• Annual health support budget up to $1,000 for medical insurance or healthcare expenses
• Workplace support allowance up to $1,000 every three years for home office or co-working setup
• Internal rewards system with redeemable bonuses for perks, experiences, and team activities
• Access to a globally distributed, innovation-driven engineering culture with continuous learning opportunities
  
  

How Jobgether Works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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