Mid/Senior AI LLM Engineer (Full Remote - Europe)
Our Vision & Products
🚀 EverAI — Building the Future of AI Companionship
One of the Top 15 Largest & Fastest-Growing AI Companies in the World
50 Million Users in 2 years — Help Us Reach 100M first, 500M next
At EverAI, we’re shaping what it means to connect with AI. With 50 million users and counting, we're not just building products — we're creating entirely new categories.
Our flagship product is the world’s largest AI companionship platform, redefining relationships for millions. It is governed by our proprietary moderation system, EverGuard — an internal AI designed to ensure everything we build is safe, ethical, and human-first.
And we’re only just getting started!
Our Team
We are an enthusiastic, passionate and hardworking team of ≈ 100 people. Our founding team has strong entrepreneurial experience building and scaling web products from 0 to IPO.
Alexis Soulopoulos [CEO]
• 10+ years in Tech Executive Leadership
• Co-Founder Mad Paws Holdings (from 0 to IPO)
• Forbes 30 under 30 + Deloitte TechFast50 ’22 & ‘23
Michael Monin [Co-founder & CTO]
• 10+ years as CTO / COO (web2/web3), 3 years in AI/LLM
• Serial-entrepreneur: MTK Digital (exited / 0->$20m revenue) and Zipchat (AI Chatbot for E-commerce brands)
Thomas Lacroix [Co-founder & CMO]
• 8+ years in Customer Acquisition & E-commerce Growth
• Serial-entrepreneur: Curatible (sold to Blackstone) and MTK Digital (exited / 0->$20m revenue)
Maruša Fasano [CFO/Legal]
• 25+ years in Finance, Strategy, M&A
• Ex-CFO/M&A @Curatible (exited to Blackstone)
• Ex-President of the Board @SotremoSA (exited)
• Co-founder/CFO @SoftOne (exited)
Your Role
Most LLM roles stop at experimentation.
Here, the models you improve power experiences for 50M+ users.
Most of our traffic runs on self-hosted, fine-tuned open-weight models. On our internal roleplay evals, our smaller fine-tuned models can outperform much larger off-the-shelf models. Your job is to make them better.
You’ll join a small AI team led by Marco, our LLM Tech Lead, working closely with our CTO, Product, Web and DevOps teams. You’ll work across data, post-training, evals, and model behavior, taking ideas from failure analysis to production.
The problems are real: personalization, character consistency, long conversations, better evals, multilingual behavior, and faster training cycles.
If you want to shape model behavior at consumer scale, this is the role.
Key Responsibilities
Fine-tune open-weight LLMs using SFT, LoRA/QLoRA and post-training methods such as DPO and GRPO
Diagnose model failures and turn them into experiments. Decide whether the answer is better data, post-training, prompting or classifiers
Build training data and evals that directly shape what gets trained next
Improve model behavior across personalization, consistency, tone, multilingual and group interactions
Ship to production and use real user behavior to guide the next iteration
Speed up the training loop so experiments are faster, easier to compare, and more reproducible
Your Qualifications
You’ve personally post-trained open-weight LLMs for a user-facing product and shipped them to production
You’ve worked where AI was core to the product or business, not an experimental side feature
Fine-tuning is core to your experience
Strong Python, PyTorch and Hugging Face, with hands-on GPU training and debugging
You build data and evals yourself and make decisions from evidence
You can take work beyond notebooks into production
You use AI tools daily in your own engineering work
You are fully comfortable working with uncensored models and explicit NSFW content, including harmful material when developing and evaluating moderation system
Bonus points
Experience with conversational AI, roleplay products, or highly personalized consumer AI
Multilingual LLMs
Moderation, safety, or adversarial testing
Multimodal models
Open-source LLM / post-training contributions
Why EverAI?
📈 Exponential Growth: From 50M users in 2 years, to 100M next — and 500M beyond
🚀 Track Record of Category-Creating Innovation: We consistently launch world-first AI applications — setting the pace, not following it