Head of Machine Learning

United Tech is a global IT product company shaping the future of real-time social connection. With millions of users across North America, Europe, LATAM, and MENA, we build next-gen mobile and web apps for live-streaming and social networking. Our platforms enable connection at scale fast, interactive, and deeply engaging. The market is projected to exceed $206B by 2030, and we are already leading the evolution. Founded in Ukraine, scaling worldwide. Are you in?

About the role: This is a role for a leader who thrives in a fast-moving product environment, where challenges fuel growth and every decision shapes the future. With United Tech you will have the freedom to design, build, and re-engineer processes from the ground up, working side by side with a team that values initiative, knowledge sharing, and bold goals. Your ideas will directly influence revenue, and you will see the tangible results of your work reflected in key financial metrics. We move fast, we cut through bureaucracy, and we take on complex challenges that push both personal and professional boundaries, limited only by the scale of your ambitions.

In this role, you will

• Build, scale, and develop the Machine Learning team, including hiring, mentoring, and performance evaluation

• Define and execute a Machine Learning strategy aligned with business priorities, and plan the department’s roadmap

• Identify and drive new ML initiatives

• Analyze existing algorithms and define the best ways to improve them

• Prioritize initiatives based on business impact (ROI, time-to-market)

• Oversee the full lifecycle of ML projects, from problem formulation to deploying models into production, ensuring execution and quality of results

• Stay hands-on: contribute directly to the implementation of key ML projects

• Provide regular reporting to stakeholders on a weekly, monthly, and quarterly basis

• Collaborate closely with product managers, analysts, engineers, and C-level executives

It’s all about you

• Proven ability to implement best practices in Data Science: reproducibility, A/B testing, ML monitoring

• Strong track record in maintaining model quality (performance, drift, latency)

• Advanced Python skills (pandas, sklearn, numpy, xgboost; pytorch/tf is a plus)

• High-level SQL expertise (large datasets, query optimization)

• Hands-on experience with ML pipelines, orchestration (Airflow, Prefect), and monitoring (Evidently, MLflow, Prometheus)

• Experience with GCP

• Solid understanding of A/B testing, causal inference, and statistics

• Familiarity with architecture fundamentals (API, data pipelines, microservices — integration level)

• Cloud experience with AWS or Azure

• Knowledge of distributed computation tools (e.g., Spark, CloudRun)

• Proven track record with generative AI/NLP model deployment

• Experience in startups or high-growth companies

• Publications, conference speaking, achievements on Kaggle, or open-source contributions

Would be a plus

• Experience optimizing company processes through AI solutions

• Implementation of AI tools across departments (development, support, marketing, etc.)

What we offer

Care and support

• 20 paid vacation days, 15 sick leave days, and 6 additional days off for family events

• 100% medical insurance coverage

• Sports and equipment reimbursement

• Team building events, corporate gifts, and stylish merch

• Financial and legal support

• Maternity Recovery Support Allowance

• Position retention and support for those who join the Armed Forces of Ukraine

• Participation in social initiatives supporting Ukraine

Comfortable working environment

• Work from our Kyiv hub or remotely with a flexible schedule

• Modern equipment or depreciation of your own tools

Investment in your future

• Collaborate with a highly-skilled team of Middle & Senior professionals, sharing practical cases and expertise in the social networking niche

• 70% of our heads and leads have grown into their roles here – so can you!

• Performance-oriented reviews and Individual Development Plans (IDPs)

• Reimbursement for professional courses and English classes

• Corporate library, book club, and knowledge-sharing events

Hiring process

• Intro call

• Technical Interview

•

ML System Design Interview

• Final Interview

• Reference check

• Offer