Machine Learning Engineering Team Lead

Deeplab combines high-end software technologies with state-of-the-art machine learning and data science research to provide services and products to deal with challenging real-life problems. This is a chance for you to join a dynamic, rapidly evolving ML/AI organization committed to research, innovation and excellence with a culture that bridges the gap between academic rigor and entrepreneurial agility. We foster an environment where the methodical, research-driven pursuit of knowledge meets innovative, fast-paced decision-making. This synergy fuels our pursuit of excellence and innovation in practical real-life problems.

The Team

We are currently expanding our Recommender Systems teams, part of an international research and development partnership with a world-leading AdTech platform. Our teams deal with disruptive projects from ideation to productization, combining innovative ML concepts with cutting-edge production technologies, within a system that serves millions daily users. You will be joining an interdisciplinary team comprising passionate ML engineers with backgrounds in both research and software development.

The role

We seek an outstanding and enthusiastic Machine Learning Engineering Team Lead with an exceptional engineering background and proven team-leading record, who shares our passion for challenging problem-solving applied to industrial problems. You will get a chance to lead one of our talented ML teams, a key part of a high-impact and production-oriented R&D department, and find great opportunities to further develop yourself and Deeplab. 

Candidates should have a proven machine learning background, as well as in-depth understanding and hands-on practical experience in production-grade development and big data tools. Additionally, candidates are expected to have experience leading an ML team in at least one relevant domain dealing with real-world data (RecSys, e-Commerce, Computer vision, NLP, etc.) and also previous hands-on experience as engineers.

Responsibilities

1. Lead, mentor, and manage a team of machine learning engineers.
2. Combine business concepts with ML-centric solution design to improve product KPIs
3. Oversee the planning, execution, and delivery of machine learning projects.
4. Be able to extract actionable insights through data analysis
5. Coordinate with cross-functional teams to align project goals with business objectives.
6. Communicate complex technical concepts to technical & non-technical stakeholders.
7. Provide regular updates on project progress, challenges, and solutions.
8. Identify opportunities for leveraging machine learning to drive business value.
9. Develop long-term strategies for ML initiatives within the organization.
10. Encourage continuous learning and improvement within the team.
11. Foster a collaborative and inclusive team environment.
12. Stay updated with the latest advancements in machine learning methodologies to ensure Deeplab's solutions remain at the cutting edge.

Requirements

1. MSc (Electrical & Comp. Eng., Machine Learning, CS), and experience in implementing and benchmarking machine learning algorithms for real-world data.
2. 5+ total years of industrial or academic experience in machine learning projects in areas such as deep learning, core ML, computer vision, natural language processing etc.
3. 2+ years (out of aforementioned 5) proven experience in leading and managing ML engineering teams.
4. Familiar with development processes using Linux, versioning, CI/CD, Docker etc.
5. Candidates should be proficient in Python, with experience developing, testing, and maintaining production-grade machine learning applications using frameworks such as TensorFlow or PyTorch.
6. Strong understanding of statistical and mathematical principles underlying machine learning algorithms.
7. Ability to analyze complex problems and develop innovative solutions.
8. Ability to build strong relationships in a challenging international environment.
9. Excellent written and oral communication skills; ability to present complex analyses in a clear, concise and actionable manner.
10. Nice to have: experience with large scale cluster computing for machine learning modeling.
11. Nice to have: Experience in sectors like e-commerce or RecSys.

Benefits

1. Supplementary private health insurance.
2. Flexible working hours and remote work from home.
3. Working in high-end AI-tech and having an impact in real-world applications.
4. Budget for home office equipment to ensure a productive and efficient workspace.
5. Personal growth opportunities through internal knowledge sharing and self-development budget.
6. Newly designed inspirational and fresh working environment at our new offices.
7. Competitive salary depending on qualifications, expertise and experience.