Staff Research Team Lead

This is a fully remote position, open to applicants in Poland.

📋 Description

• Lead a small team of 4–8 machine learning researchers while remaining actively involved in hands-on work.

• Establish direction, set priorities, review team outputs, remove obstacles for team members, and foster career development.

• Maintain a balance between hands-on research and team leadership, approximately a 50/50 split.

• Identify, define, and spearhead company-wide research initiatives that influence core metrics.

• Design and implement deep neural network models to predict Internet user behavior and preferences.

• Develop and test modeling techniques for challenges such as bidding in first-price auctions.

• Conduct and analyze A/B tests.

• Stay updated on machine learning research and translate insights into actionable improvements.

• Mentor researchers and influence research methodologies across teams.

• Oversee projects from inception through analysis, proof of concept, testing, implementation, and deployment.

⛳️ Requirements

• Minimum of 5 years of experience as a researcher or engineer.

• At least 2 years of hands-on experience in machine learning or data science.

• A minimum of 2 years of experience in managing and mentoring an engineering or research team.

• Proficiency in programming.

• Strong mathematical knowledge and intuition.

• Exceptional individual contributor skills in applied machine learning research.

• Ability to tackle ambiguous problems and set measurable objectives.

• Practical experience in writing code, training models, conducting experiments, and deploying machine learning systems.

• Skills in team leadership, project prioritization, stakeholder communication, and mentorship.

• Experience in AdTech is advantageous but not mandatory.

• A strong foundation in theoretical mathematics, experience in hiring and building research teams, and experience leading applied research in a production setting are beneficial.

🏝️ Benefits

• Access to cutting-edge technologies and the chance to utilize them in large-scale, dynamic projects.

• Work with extensive and diverse datasets.

• Options for remote or on-site work.

• Flexible working hours.

• Opportunities for knowledge sharing and learning within a seasoned machine learning team.

• Engage in practical work that directly impacts business results.