Senior Machine Learning Engineer
Cresta
full-time
Posted on:
Location Type: Remote
Location: Germany
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Job Level
Tech Stack
About the role
- Design, implement, and maintain evaluation frameworks to measure model accuracy, robustness, latency, and real-world performance across ASR and NLP systems.
- Lead ASR quality improvement efforts, including error analysis, dataset curation, metric definition (e.g., WER and task-specific metrics), and model iteration.
- Analyze large-scale speech and text data to identify failure modes and drive targeted model and data improvements.
- Develop, train, and deploy machine learning models for speech recognition and downstream tasks such as classification, entity recognition, information extraction, and structured insight generation.
- Partner with applied research to translate experimental improvements into production-ready systems.
- Collaborate with product managers, platform engineers, and UX teams to align model quality metrics with customer and business goals.
- Optimize ML pipelines and evaluation workflows to operate efficiently and reliably at scale.
- Establish best practices for model validation, offline/online evaluation, and continuous quality monitoring in production.
Requirements
- Master’s or Ph.D. in Computer Science, Machine Learning, AI, or a related field.
- 5+ years of hands-on experience building, evaluating, and deploying ML models in production.
- Strong background in speech recognition (ASR), speech processing, or closely related domains.
- Deep experience with model evaluation, benchmarking, and error analysis for ML systems.
- Proficiency with ML frameworks and libraries (e.g., PyTorch, TensorFlow, Hugging Face).
- Solid understanding of modern ML techniques, including transformer-based models and large-scale training.
- Experience building data pipelines and tooling for large-scale experimentation and quality analysis.
- Strong passion for improving real-world AI system quality, with a track record of delivering measurable, production-grade improvements.
Benefits
- Compensation for this position includes a base salary, equity, and a variety of benefits.
- Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningmodel evaluationerror analysisdataset curationmodel iterationspeech recognitionclassificationentity recognitioninformation extractionstructured insight generation
Soft Skills
leadershipcollaborationcommunicationproblem-solvinganalytical thinking
Certifications
Master’s in Computer SciencePh.D. in Machine LearningPh.D. in AI