[Hiring] Senior ML Engineer @Social Discovery Group

Role Description

We are looking for a 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.

Qualifications

• Python expert level: clean code, typing, async, multiprocessing, profiling, debugging, notebooks + production code.
• Transformers.
• 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.

Requirements

• Experience beyond text (computer vision, image generation, multimodal), long-running conversations and character consistency, vLLM / TGI / SGLang, DeepSpeed / FSDP / Accelerate, quantization, safety classifiers.

Benefits

• 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.
• Corporate discount for English lessons.
• Health benefits: up to $1,000 gross per year per employee for health insurance or doctor’s fees for yourself and close relatives (spouse, children).
• Workplace organization: equipped workplace and necessary equipment provided in offices or co-working locations; reimbursement of workplace costs up to $1000 gross once every 3 years for remote setups.
• Internal gamified gratitude system: receive bonuses from colleagues and exchange them for merchandise, team building activities, massage certificates, etc.