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Machine Learning Lead (Dialogue Systems & LLM)

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AI Summary

Lead the machine learning strategy for dialogue systems at Social Discovery Group, owning roadmap decisions tied to business metrics like ARPU, retention, and chat depth. Manage and grow a team of 3 ML engineers while driving LLM post-training (SFT, LoRA/QLoRA, DPO/ORPO/SimPO/GRPO), agent harnesses, tool-using LLM systems, and robust evaluation frameworks. Requires a technical degree, hands-on ML engineering background, expert-level Python, production LLM systems experience, fluent Russian, and availability to work in CET (±2) hours.

Key Highlights
Own the ML strategy for dialogue systems, tying technical bets to business metrics (ARPU, retention, chat depth)
Lead a team of 3 ML engineers, including hiring, performance decisions, and people development
Drive LLM post-training end to end: SFT, LoRA/QLoRA, preference optimization, and dataset construction
Fully remote position with a fully international, remote-first team
Stay hands-on with roughly 10–20% of time on prototypes, debugging, and code review
Key Responsibilities
Own the ML strategy for dialogue systems, deciding what to build and in what order, tied to business metrics (ARPU, retention, chat depth)
Lead a team of 3 ML engineers: set the technical bar, distribute work, hire, let go, and grow team members
Drive LLM post-training and model adaptation end to end: SFT, LoRA/QLoRA, preference optimization (DPO/ORPO/SimPO/GRPO), and dataset construction
Design agent harnesses and tool-using LLM systems: tool calling, structured outputs, routing, retries, memory and context, guardrails
Build the evaluation layer: offline and pairwise evals, LLM-as-a-judge, and regression suites correlated with A/B outcomes
Reduce dialogue failure modes such as loops, contradictions, persona drift, context loss, and generic replies while keeping inference efficient on latency and cost
Stay hands-on (10–20% of time) with prototypes, debugging agent traces, and reviewing team work
Technical Skills Required
Python Large Language Models (LLM) Machine Learning
Benefits & Perks
Fully remote full-time opportunity
28 calendar days of vacation per year
7 wellness days per year
Bonuses up to $5000 for successful referrals
50% payment for professional training, international conferences, and meetings
Corporate discount for English lessons
Health benefits compensation up to $1,000 gross per year if not eligible for corporate medical insurance
Workplace organization: equipped office/co-working space or reimbursement up to $1,000 gross once every 3 years
Internal gamified gratitude system with bonuses exchangeable for merchandise and activities
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

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 Lead.

Your Main Tasks Will Be

  • Own the ML strategy for dialogue systems: decide what to build and in what order, and tie those bets to business metrics (ARPU, retention, chat depth).
  • Lead a team of 3 ML engineers — set the technical bar, distribute work, hire and let go, grow the people you keep.
  • Drive LLM post-training and model adaptation end to end: SFT, LoRA/QLoRA, preference optimization (DPO / ORPO / SimPO / GRPO), dataset construction.
  • Design agent harnesses and tool-using LLM systems: tool calling, structured outputs, routing, retries, memory and context, guardrails.
  • Build the evaluation layer: offline and pairwise evals, LLM-as-a-judge, regression suites that actually correlate with A/B outcomes.
  • Cut dialogue failure modes — loops, contradictions, persona drift, context loss, generic replies — and keep inference efficient on latency and cost per message.
  • Stay hands-on where it matters (roughly 10–20% of your time): prototypes, debugging agent traces, reviewing your team's work.

We Expect From You

  • Technical degree and a real ML engineering background — you have trained and shipped models yourself, not only managed people who do.
  • Experience leading a team of 3–5 ML engineers, including hiring and performance decisions.
  • Expert-level Python, solid understanding of transformer architecture and modern LLM behavior, hands-on with training, fine-tuning and evaluation.
  • Production experience with LLM systems: APIs, streaming, batching, fallbacks, cost/latency trade-offs, observability over traces and transcripts.
  • Ability to read fresh research and turn it into a prototype, an eval and a shipped change with measurable impact.
  • 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;
  • 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.

Sounds good? Join us now!

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