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

- **Company:** Social Discovery Group
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Computer Vision, BASIC (Programming Language), Profiling, Nvidia CUDA, Data Deduplication, Software Debugging, Linux, Python (Programming Language), Multiprocessing, Data Streaming, QLoRA, DeepSpeed, Transfer Learning, Large Language Models, Multi-Agent Systems, Generative AI, Git, Build Management, SGLang, Machine Learning Operations, Evaluation of Large Language Models, Invoking Functions, Docker
- **Published:** November 9, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/py05fq9a5d

## About the Role

* 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.

## Description

* 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:

 * Python expert level: clean code, typing, async, multiprocessing, profiling, debugging, notebooks + production code.Trainsformers.
 * 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., * 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;
 * Corporate discount for English lessons;
 * 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.