Omegga - Senior Deep Learning Engineer (m/f/d)
Requirements
• Experience with domain adaptation and evaluation in imbalanced settings (rare events, high cost of misses/false alarms). • domain adaptation • imbalanced settings • 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. • time-series • Experience with agentic AI development workflows to speed up experimentation (analysis, ablations, test scaffolding) while maintaining careful review and scientific rigor. • agentic AI development workflows • What You’ll Get • What You’ll Get • Mission & Technical Challenge: At Omegga, you work on problems that are both technically demanding and globally relevant. We build deep-tech solutions with real-world impact, pushing the boundaries of what's currently possible. • Mission & Technical Challenge: • Relocation Support: Moving to Munich? We help you find an apartment in the Werksviertel within walking distance of the office. We connect you with the right contacts and take the stress out of apartment hunting. • Relocation Support: • Work Environment: Located in Munich's Werksviertel, we combine a focused, high-performance culture with flexibility. Up to 50% remote work, depending on role and execution needs. • Work Environment: • Ownership: VSOPs (Virtual Stock Options) so you share in the value you help create. • Ownership: • Time Off: 28 vacation days per year, plus December 24th and 31st off. • Time Off:
Responsibilities
• 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. • Advance our deep learning models through research 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. • Build rigorous evaluation and benchmarks: • 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. • Own monitoring of model quality: • 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. • Partner cross-functionally to turn findings into impact: • Your Profile: Qualifications & 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. • MSc in Computer Scienc • 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). • modern neural architectures, • transformer architectures • 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. • experiment tracking and model evaluation tooling • Fluency in English, German is a plus
Benefits
• 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
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