Social Discovery Group

Middle ML Engineer

Remote Remote Worldwide
Streaming Kubernetes Kafka Docker Python SQL Deep Learning
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Description

Social Discovery Group (SDG) is a global technology company that builds apps at the intersection of dating, social, and entertainment. The company's portfolio includes 70 social discovery platforms with a focus on AI, game mechanics, and video streaming. We actively support and invest in social discovery startups worldwide through our CVC fund.

More than 500 million people in 150 countries enjoy our products, and we strive to have ten times as many.

SDG invests
in social discovery technology startups around the world. Our Investments include Open AI, Patreon, Flo, RAW, EVA AI, Clubhouse, Magnet, Woebot, Flure, Astry, Coursera, Academia, Harbour, Space, Auto1, DocSend, AppAnnie, Rapyd, Boom Supersonic, Trading, View, K-Health and many others.

We solve the problem of loneliness, isolation, and disconnection with the help of digital reality.

Our digital nomad team of more than 1200 professionals works all over the world. Together, we are solving the prevalent problem of loneliness and shaping Social Life 3.0 — a new digital reality where people will be able to fulfil their needs for communication and attention from other people and artificial life forms.

Our teams of digital nomads live and work remotely from Cyprus, Malta, the USA, Thailand, Indonesia, Hong Kong, Japan, Australia, Poland, Israel, Turkey, Latvia and many others.

We are looking for a Middle ML Engineer.

As a Middle ML Engineer on this position you will be responsible for ownership of various tasks/projects concerning communication activity on our sites and other ML for core business tasks. Among current large projects there are recommendation system, chat bot for support, moderation service and a large pool of marketing projects. Your future focus will be in a marketing area, but if you are full of ideas and skills, you alway be supported for pushing great ideas to live. In your team there will be several Ml engineers, MlOps and devs to help with infrastructure or simply discuss approaches.

MlOps stack: Kubernetes, Mlflow, Bento, S3, Kafka, Arize

Your daily activities:

  • Owe a particular projects from the data to the prod;
  • Build ML/AI models, write services (if needed for the project), wrap them into Docker;
  • Cheer to success of your project : )

        We expect from you:

        • A 2+ years in developing ML models;
        • Proficiency in Python, SQL, deep learning libraries;
        • Excellent coding skills;
        • Familiarity with Data & ML production pipelines: Airflow, MlFlow, Bento;
        • Understanding which algorithm suits better for particular task.

        Nice to have hard skills:

        • Expirience in building MMM models;
        • Time series forecasting skills.

          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;
          • Full payment for professional training, international conferences and meetings;
          • Corporate discount for English lessons;
          • Health benefits. If you are not eligible for corporate medical insurance, the company will compensate you with up to $ 1,000 gross per year per employee, according to the paychecks. 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 time off, merch, team building activities, massage certificates, etc.

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