Senior ML Engineer (LLM Fine-tuning) - Full remote

Dating Group; España; Remote; EUR 60,000 - 95,000; Full time

Benefits offered by this job

Remote opportunity

Vacation 28 days per year

Wellness days 7 per year

Bonuses up to $5000 for referrals

50% payment for professional training

Job summary

Social Discovery Group (SDG) is seeking a Machine Learning Engineer to direct ML strategy and lead end-to-end LLM projects. You will design agent harnesses, optimize preferences, and implement production LLM systems that shape user experience and monetization.

The role requires deep knowledge of transformers, LLM evaluation, and MLOps. Remote work is available with CET-hour alignment and competitive compensation.

Qualifications

• Experience in training and fine‑tuning LLMs.
• Familiar with SFT, LoRA/QLoRA, PEFT.
• Proficiency in dataset construction and preference optimization.
• Experience with LLM evaluation and human annotation.
• Ability to design agent harnesses and tool‑using LLM systems.
• Proven track record in production LLM integration and API usage.
• Strong understanding of transformer architectures and modern LLM behavior.
• MLOps basics (Git, Docker, Linux) and remote work readiness.
• Russian language proficiency; CET hour alignment required.

Responsibilities

• Set the ML direction and tie bets to business needs.
• Drive end-to-end LLM post-training and model adaptation.
• Design and build agent harnesses and tool‑using LLM systems.
• Shape multi‑agent workflows to improve speed and quality.
• Build evaluation frameworks and LLM‑as‑a‑judge systems.
• Improve dialogue quality across memory, personality, safety, and anti‑loop behavior.
• Ship production systems that impact user experience and monetization.

Skills

LLM training

LoRA/QLoRA

PEFT

Preference optimization

Dataset construction

LLM evaluation

Agent harness design

Production LLM integration

Observability

Transformer architecture

MLOps basics

Git

Docker

Linux

Russian language

Tools

Git

Docker

Linux

Job description

Social Discovery Group (SDG) is a group of social discovery companies. SDG solves the problems of loneliness, isolation, and disconnection - transforming virtual intimacy into the new normal. SDG’s products redefine the way people interact and connect with one another.

Our portfolio includes social entertainment platforms designed to connect people online across different cultures and regions of the world.

We bring together a team of like‑minded people and IT professionals who specialize in creating and developing globally impactful social discovery products. Our international team of digital nomads works remotely from all over the world.

We’re proud to be a two-time “Great Place to Work” winner (USA & Japan, 2024–2025) and a Top-5 Company for Work-From-Anywhere Jobs (FlexJobs, 2025).

We are looking for Machine Learning Engineer.

Your main tasks will be:

• Set the ML direction: choose which strategic bets to make and tie each one to clear business needs.
• Drive LLM post-training and model adaptation end to end, from dataset construction to fine‑tuning and preference optimization.
• Design and build agent harnesses and tool‑using LLM systems.
• Shape multi‑agent development workflows that make the team faster and more effective.
• Build evaluation frameworks and LLM‑as-a‑judge systems that reliably predict real‑world performance.
• Improve dialogue quality across memory, emotional intelligence, persona consistency, safety and anti-loop behavior.
• Ship production systems that directly shape user experience, retention and monetization.

We expect from you:

• Training and fine‑tuning LLMs.
• SFT, LoRA/QLoRA, PEFT.
• Preference optimization: DPO / ORPO / SimPO / CPO / GRPO or willingness to quickly go deep.
• Building datasets for LLM training: cleaning, filtering, deduplication, preference pairs, synthetic data, hard negative mining.
• LLM evaluation: offline evals, pairwise evals, LLM judges, human annotation.
• Agent harness design: tool calling, function calling, structured outputs, retries, routing, state management, memory/context, guardrails.
• Production LLM integration: APIs, streaming, batching, fallbacks, cost/latency trade‑offs.
• Observability for agents: traces, tool‑call logs, transcript analysis, failure clustering.
• Strong understanding of transformer architecture and modern LLM behavior.
• Accuracy with dtype/device/batching: fp32/fp16/bf16, quantization, CUDA memory, avoiding dtype mismatch bugs.
• Git, Docker, Linux, basic MLOps.
• Fluent Russian, ready to work in CET (±2) hours.

Nice to have: experience beyond text (computer vision, image generation, multimodal), long‑running conversations and character consistency, vLLM / TGI / SGLang, DeepSpeed / FSDP / Accelerate, quantization, safety classifiers.

What do we offer:

• REMOTE OPPORTUNITY to work full‑time;
• The initial pay level or pay range for this role will be shared with candidates during the recruitment process and before the commencement of employment;
• Vacation 28 calendar days per year;
• 7 wellness days per year (time off) that can be used to deal with household issues, to lie down and recover without taking sick leave;
• Bonuses up to $5000 for recommending successful applicants for positions in the company;
• 50% payment for professional training, international conferences, and meetings;
• Health benefits. According to the paychecks, if you are not eligible for corporate medical insurance, the company will compensate you with up to $ 1,000 gross per year per employee. This can be spent on self‑purchase of health insurance or on doctor’s fees for yourself and close relatives (spouse, children);
• Workplace organization. The company provides all employees with an equipped workplace and all the necessary equipment (table, armchair, wifi, etc.) in our offices or co‑working locations. In the other locations, the company provides reimbursement of workplace costs up to $ 1000 gross once every 3 years, according to the paychecks. This money can be spent on the rent of the co‑working room, on equipping the working place at home (desk, chair, Internet, etc.) during those 3 years;
• Internal gamified gratitude system: receive bonuses from colleagues and exchange them for our merchandise, team building activities, massage certificates, etc.