Senior Deep Learning Engineer

Company: Omegga

About the job

At Omegga, we’re on a mission to reinvent how AI and science can drive positive change for animals, people and the planet.

Five years ago, we began in the poultry industry with a bold idea: use breakthrough AI-powered spectroscopy to revolutionise the industry by identifying chick gender before hatching to spare billions of male chicks.

With the support of our customers, investors and the European Commission, we are ready for the next chapter in poultry while exploring new applications. Join us and help shape a future where innovation drives meaningful change.

Requirements

• MSc in Computer Science or a related field with 4+ years of applied deep learning experience, or a PhD — paired with a proven track record of taking research from idea to working system.
• Strong understanding of modern neural architectures, with demonstrated depth in transformer architectures and practical experience improving and adapting them (e.g., attention variants, efficiency improvements, robustness, training stability).
• Strong Python deep learning stack experience (e.g. PyTorch, Tensorflow), including training pipelines, experimentation discipline, and reproducibility.
• Solid experience with experiment tracking and model evaluation tooling (e.g. Weights & Biases or similar), and a strong bias for measurement-driven progress.
• Fluency in English, German is a plus

Nice to have

• Experience with domain adaptation and evaluation in imbalanced settings (rare events, high cost of misses/false alarms).
• Familiarity with deployment-adjacent concerns: model packaging, performance constraints, and continuous evaluation in changing real-world conditions.
• Experience working with sensor/time-series or industrial data, where edge cases and dataset shifts are the norm.
• Experience with agentic AI development workflows to speed up experimentation (analysis, ablations, test scaffolding) while maintaining careful review and scientific rigor.

The candidate

• Advance our deep learning models through research iteration: develop and test architectural improvements, training objectives, and optimization techniques. You will own the loop from idea → experiment → conclusion → next iteration.
• Build rigorous evaluation and benchmarks: define evaluation sets, establish clear metrics (precision, recall, accuracy, calibration), and create repeatable benchmark runs so improvements are measurable and comparable over time.
• Own monitoring of model quality: set up monitoring for model performance and data shifts, define alerting signals, and build lightweight reporting that makes regressions visible early.
• Partner cross-functionally to turn findings into impact: work with data/engineering teams to improve datasets and labeling strategies, and with product/ops stakeholders to align on what “good” looks like in practice.

What we offer

• Monthly meal budget for whatever keeps you going, from quick lunches to proper team dinners
• Monthly perks budget to spend where it actually matters to you — fitness, mobility, or the occasional "I earned this" purchase
• Annual learning budget to invest in your growth, from conferences to deep dives into new domains
• Free drinks, coffee, and snacks in the office to keep you focused throughout the day
• Time Off: 28 vacation days per year, plus December 24th and 31st off.

Experience level: Senior

How to apply: send your CV and motivation to [email protected]