Machine Learning Lead

Social Discovery Group; España; On-site; PHP 7,524,000 - 11,285,000; Full time

Benefits offered by this job

Remote role

Vacation 28 days

Wellness days

Bonuses up to $5000 for referrals

Training stipend 50%

English lesson discount

Health benefits up to $1000

Home office stipend up to $1000 every

Job summary

Social Discovery Group (SDG) seeks a Machine Learning Lead to own the ML strategy for dialogue systems and align bets with business metrics. You will manage a team of 3 ML engineers, drive post-training and model adaptation, and design agent harnesses with tool-using LLM systems.

The role requires hands-on work (10–20% time) on prototypes, debugging traces, and ensuring low latency and cost. Fluent Russian and CET-friendly hours are expected.

Qualifications

• Technical degree and 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, strong 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.
• Ability to read fresh research and translate it into prototypes, evaluations and shipped improvements with measurable impact.
• Fluent Russian, ready to work in CET (±2) hours.

Responsibilities

• Own the ML strategy for dialogue systems: decide what to build and in what order, tied to business metrics.
• Lead a team of ML engineers; set the technical bar, distribute work, hire and grow the team.
• Drive LLM post-training and model adaptation end to end: SFT, LoRA/QLoRA, preference optimization, dataset construction.
• Design agent harnesses and tool-using LLM systems: tool calling, structured outputs, routing, retries, memory, guardrails.
• Build the evaluation layer: offline and pairwise evals, LLM-as-a-judge, regression suites tied to AB outcomes.
• Cut dialogue failure modes and keep inference efficient on latency and cost per message.
• Stay hands-on where it matters (10–20%): prototypes, debugging traces, reviewing team work.

Skills

Python

Transformer models

LLM systems

Team leadership

Hiring decisions

Research-to-prototype

Russian language

Education

Technical degree

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).

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.