[All remote jobs](https://jobicy.com/jobs.md)[![EverAI logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/91735b0b-221.png)](https://jobicy.com/company/everai.md)[EverAI](https://jobicy.com/company/everai.md) # Mid/Senior AI LLM Engineer (Full Remote – Germany) AI Summary EverAI is seeking a mid/senior LLM engineer to improve and operate self-hosted, fine-tuned open-weight language models powering a large consumer AI platform. The role covers training-data development, SFT and parameter-efficient fine-tuning, preference optimization, evaluation design, failure analysis, and production deployment. The engineer will work closely with LLM leadership, product, web, and DevOps teams to improve personalization, consistency, multilingual behavior, and conversational quality. This is a high-ownership remote position requiring hands-on GPU training, strong Python/PyTorch skills, and comfort evaluating uncensored and explicit content for moderation and safety work.[Apply for this job](#job-application)[View company](https://jobicy.com/company/everai.md)ShareRemote from[Germany](https://jobicy.com/job-region/germany.md), [Portugal](https://jobicy.com/job-region/portugal.md)SalaryEUR 75k–125k / yrDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceDirectorPublished7 Nov 2026Apply before7 Dec 2026Listing views28Application actions1Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. Opportunity details ## About this role. ### Our Vision & Products 🚀 [EverAI](https://jobicy.com/company/everai.md) — 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 🌍 Global Impact: Top-tier user growth, real-world adoption, and cultural relevance 🧠 Proven Leadership: A senior team that’s launched, scaled, and exited & IPO’d multiple scale ups — now fully focused on reshaping AI companionship 👥 Elite Remote Team: 100% remote and built to win — world-class talent from Tier 1 tech companies, with a culture of ownership, velocity, and radical creativity 🛡️ Ethical Core: Our AI ecosystem is governed by EverGuard, our proprietary AI moderation technology, ensuring responsible development at scale ### What We Offer ✍️ Contract Type: We prefer B2B, but we’re flexible, what matters is long-term commitment and impact 📍 Work From Anywhere: Fully remote. Choose the environment where you do your best work 🏝️ Paid Time Off: 4 weeks (20 working days) of PTO per year to recharge and reset 👨‍👩‍👧‍👦 Annual Gathering: A yearly in-person meetup to connect, brainstorm, and celebrate wins together ❤️‍🩹 Health & Wellness Support: Monthly allowance of 100 USD for health insurance expenses & access to unlimited 1:1 sessions with psychologists and lifestyle experts through OpenUp (also available to up to three of your family members) 🏢 Co-Working Space Budget: Work from a co-working space up to twice per month (35 EUR / 40 USD per visit) to stay inspired and connected 📚 Learning Budget: Dedicated funds to support your professional growth: courses, books, conferences, events, or certifications 💻 Company Laptop & Equipment: Laptop provided + monitor budget up to 250 USD + keyboard/mouse/mic/headphones budget up to 150 USD ⚡ AI Tools Access: Premium access to ChatGPT, Hugging Face, Claude Code, and any other tool needed to excel at your job, power your ideas and workflows ### 🎯 Top Tier Talent Is Our Multiplier We’re a fully remote group of A-players from Tier 1 tech, led by an exec team who’ve launched, scaled, and exited multiple companies. We move fast, and care deeply about what we build — and who we build it with. We’re looking for exceptional talent ready to ship & distribute world-first AI products at scale, fast, and co-create with us this category-defining business. If that’s you — reach out and apply! Show more [Apply now >](https://jobicy.com/jobs/159582-mid-senior-ai-llm-engineer-full-remote-germany.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThe position requires demonstrated production experience post-training open-weight LLMs, debugging GPU training workflows, and making evidence-based decisions across data, evaluations, prompting, and classifiers. The models serve a high-scale consumer product, so iteration quality, reliability, and speed are critical. ## Salary analysis Estimated compensation compared with the broader EU market for similar roles. Estimated job median (per year)Market rate€100,000EU market range (per year)€85k–€135k0€148.50k AI insightThe employer discloses a yearly base compensation range of €75,000–€125,000, with a midpoint of €100,000. Estimated European market compensation for a mid/senior production LLM engineer is approximately €85,000–€135,000 per year; actual pay may vary by location, B2B structure, and depth of post-training experience. ## Core skills Skills and capabilities most closely associated with this opportunity. [Large language models](https://jobicy.com/jobs?search_keywords=Large%20language%20models.md)[LLM fine-tuning](https://jobicy.com/jobs?search_keywords=LLM%20fine-tuning.md)[Supervised fine-tuning](https://jobicy.com/jobs?search_keywords=Supervised%20fine-tuning.md)[LoRA](https://jobicy.com/jobs?search_keywords=LoRA.md)[QLoRA](https://jobicy.com/jobs?search_keywords=QLoRA.md)[Direct preference optimization](https://jobicy.com/jobs?search_keywords=Direct%20preference%20optimization.md)[GRPO](https://jobicy.com/jobs?search_keywords=GRPO.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[PyTorch](https://jobicy.com/jobs?search_keywords=PyTorch.md)[Hugging Face](https://jobicy.com/jobs?search_keywords=Hugging%20Face.md)[GPU training](https://jobicy.com/jobs?search_keywords=GPU%20training.md)[Model evaluation](https://jobicy.com/jobs?search_keywords=Model%20evaluation.md)[Training data curation](https://jobicy.com/jobs?search_keywords=Training%20data%20curation.md)[MLOps](https://jobicy.com/jobs?search_keywords=MLOps.md)[AI safety](https://jobicy.com/jobs?search_keywords=AI%20safety.md) Sample interview questionsDescribe an open-weight LLM you post-trained and shipped to a user-facing production environment.I would outline the base model selection, target user behavior, data pipeline, training approach, offline evaluation criteria, deployment process, and post-launch metrics. I would also explain a concrete issue found in production and how I used it to prioritize the next iteration. How would you decide whether a recurring model failure should be addressed with data, post-training, prompting, or a classifier? I would first cluster failures by type and inspect representative examples. If the desired response behavior is stable and broadly applicable, I would favor high-quality training examples or preference data; if the issue is contextual or rapidly changing, prompting may be more appropriate; classifiers are useful for distinct safety, policy, or routing decisions. What practices make LLM training experiments reproducible and comparable? I would version datasets, prompts, model checkpoints, code, hyperparameters, and evaluation suites. I would track GPU environment details, random seeds, training curves, and standardized benchmark results, then compare experiments against a controlled baseline before promoting a candidate. How would you evaluate character consistency and long-conversation quality in a companionship product? I would create scenario-based, multi-turn evaluation sets with explicit persona facts, prior commitments, emotional context, and adversarial contradictions. I would combine automated rubric-based scoring with targeted human review and track regressions by language, conversation length, and user segment. How do you approach work involving uncensored or explicit content while building a moderation system? I would follow clear handling procedures, minimize exposure to only what is necessary for the task, and use carefully defined taxonomies and annotation guidance. I would separate model-quality objectives from safety controls, validate moderation performance with adversarial tests, and escalate ambiguous policy cases through an established review process. Next step ## Apply now. 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