ML Engineer

Social Discovery Group (SDG) is the 3rd largest social discovery company in the world, uniting 60+ brands with 500 million users. We solve the problems of loneliness, isolation, and disconnection by transforming virtual intimacy into the new normal. Our portfolio includes online communication platforms focusing on AI, game mechanics, and video streaming - Dating.com, DateMyAge, Cupid Media, Dil Mil, Kiseki, and others.

SDG invests in IT startups around the world. Our investments include Open AI, Patreon, Flo, Clubhouse, Woebot, Flure, Astry, Coursera, Academia.edu, and many others.

We bring together a team of like-minded people and IT professionals specializing in the creation and development of globally impactful social discovery products. Our international team of 1200 professionals and digital nomads works all over the world.

Our teams of digital nomads work remotely from Cyprus, Malta, the USA, Armenia, Georgia, Kazakhstan, Montenegro, Poland, Latvia, Serbia, Spain, Portugal, UAE, Israel, Turkey, Thailand, Indonesia, Japan, Hong Kong, Australia and many other locations.

In August 2024, we achieved Great Place to Work US Certification™! This achievement reflects our core belief that a truly exceptional workplace is built on trust, pride, and camaraderie—not just great perks.

We are looking for a Senior ML Engineer to join our Core team.

As an ML Engineer, you will own ML projects that improve communication activity and monetization across our products. Your main focus will be recommendation systems and user value (LTV) signals, with room to expand into adjacent areas if you want to drive new ideas. You’ll work in a team with other ML engineers, MLOps, and developers who help you ship reliably.

Your daily activities:

- Own a project end-to-end: from data and experiments to production and monitoring
- Improve existing recommender models (ranking/matching) and iterate via offline evaluation + A/B tests
- Build and refine value prediction signals (e.g., LTV@30, first purchase / conversion probability)
- Develop training and scoring pipelines; ensure data quality and reproducibility
- Deploy models to production (batch/API), package solutions into Docker, follow CI/CD practices
- Collaborate with Product and Analytics to define success metrics and turn results into product changes
- Share knowledge through code reviews, documentation, and mentoring within the team

We expect from you:

• 3+ years of hands-on classic ML development (from data exploration to production use)
  
• Strong Python for ML (pandas, NumPy, scikit-learn; solid coding and debugging skills)
• Solid understanding of ML algorithms and how to choose the right approach for a task
• Experience with recommender/ranking problems and their evaluation (offline metrics, A/B testing basics)
• SQL and experience working with large datasets
• Production ML experience: building training/inference pipelines, deployment, monitoring, Docker
• Cloud experience: AWS / GCP / Azure (at least one)

What do we offer:

• REMOTE OPPORTUNITY to work full time;
• 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!