Mid- level R&D Machine Learning Engineer

Deeplab combines high-end software technologies with state-of-the-art advanced machine learning and deep learning research to provide services and products that face challenging real-life problems. This is your chance to join a dynamic and rapidly evolving ML/AI organization committed to research, innovation, and excellence.

We foster a fresh culture that bridges academic rigor with entrepreneurial agility, creating an environment where methodical research meets real-world impact and fast-paced innovation. This synergy fuels our mission to solve complex, meaningful problems using cutting-edge machine learning.

The Team

We are currently expanding our R&D teams, dealing with disruptive high risk/high impact projects from ideation to proposal compilation, proof of concept development and final project delivery, combining innovative DL/ML concepts with cutting-edge production technologies. Projects in the overall group deal with a diverse list of topics such as adTech systems that serves millions daily users, drug discovery with virtual screening of billions of molecules, cancer immunotherapies, brain computer interfaces and so on. 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 Mid-level ML Engineer with an exceptional engineering background and proven both research and hands-on development record, who shares our passion for problem-solving applied to challenging problems. You will get the chance to work closely with ML engineers, interdisciplinary domain experts and software developers to explore, prototype, and implement proof of concepts and algorithms that address real-world problems. You will also support the technical preparation of proposals for a variety of funded research and innovation grant applications and projects. This is a great opportunity to grow technically and intellectually while making a tangible contribution to both applied ML systems and R&D initiatives.

Responsibilities

1. Design, develop and implement machine learning/deep learning algorithms.
2. Problem solving, solution formulation, DL/ML architecture and pipeline design and development. 
3. Conduct ML experimentation and benchmarking.
4. PoC development incorporating new state-of-the-art after in-depth literature survey in diverse research topics and applications.
5. Perform statistical modeling, data analytics.
6. Manage and preprocess datasets to ensure consistency and quality.
7. Optimize models for scalability and efficiency.
8. Support the planning, execution, and delivery of projects.
9. Participate in knowledge-sharing and improvement within the team.
10. Contribute to the preparation, compilation and creative writing of technical content with up to date state of the art reviews for challenging EU grant and industrial proposals.
11. Collaborate across disciplines in cross-functional international teams.
12. Stay current with ML research and developments relevant to Deeplab’s work.

Requirements

1. MSc (Electrical & Comp. Eng., Machine Learning, CS), and experience in implementing and benchmarking machine learning algorithms for real-world data.
2. Strong requirement: 2+ total years of in-depth hands-on industrial and academic experience in machine learning projects in areas such as deep learning, core ML, computer vision, natural language processing etc. Industrial experience is a requirement.
3. Strong understanding of statistical and mathematical principles underlying machine learning algorithms.
4. Candidates should be proficient in Python, with experience developing, testing, and maintaining production-grade machine learning applications using frameworks such as TensorFlow or PyTorch.
5. Experience with technical writing both in terms of research proposals and scientific/tech papers.
6. Familiar with development processes using Linux, versioning, CI/CD, Docker etc.
7. Ability to analyze complex problems and develop innovative solutions.
8. Ability to collaborate in challenging international environments.
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.

Benefits

• Supplementary private health insurance.
• Flexible working hours and remote work opportunities.
• Work in high-end AI-tech and contribute to real-world impact.
• Budget for home office equipment and productivity.
• Personal development budget and knowledge-sharing sessions.
• Newly designed and inspiring office environment.
• Competitive salary based on experience and qualifications.