What are the responsibilities and job description for the Research Engineer (Python/Pytorch) position at CSS Tec?
Role Overview
We are seeking a Research Engineer to contribute to the advancement of our core voice intelligence platform. This role is ideal for individuals who thrive in an innovative, high-impact environment and are passionate about bridging cutting-edge research with scalable production systems.
The Research Engineer will collaborate closely with applied scientists and product engineers to design, prototype, and deploy models capable of analyzing speech patterns, signal characteristics, and behavioral biomarkers at scale.
Key Responsibilities
- Design and implement machine learning models for:
- Voice biometrics and speaker identification
- Detection of synthetic or deepfake audio
- Emotional and physiological signal extraction from speech
- Develop and optimize audio signal processing pipelines, including time-frequency analysis, feature extraction, and noise robustness
- Translate research concepts into production-ready solutions
- Contribute to model evaluation frameworks, including benchmarking for accuracy, bias, and system robustness
- Work with large-scale audio datasets, including data curation, labeling strategies, and augmentation techniques
- Collaborate cross-functionally with:
- Security and product teams
- Data engineering teams
- External research partners, as applicable
- Stay current with industry advancements in:
- Speech AI (e.g., ASR, speaker verification, self-supervised learning models)
- Generative audio and deepfake technologies
- Behavioral biometrics
Required Qualifications
- Master’s or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, or a related field
- Approximately 2–6 years of professional or research experience (flexible based on depth of expertise)
- Strong programming skills in:
- Python (required)
- PyTorch and/or TensorFlow
- Experience with machine learning applied to audio or speech processing is highly desirable
- Foundational knowledge of:
- Signal processing (e.g., FFT, spectrograms, filtering)
- Feature extraction techniques (e.g., MFCCs, embeddings)
- Demonstrated experience building and evaluating machine learning models in real-world environments
- Ability to effectively balance research exploration with engineering execution
Preferred Qualifications
- Experience with:
- Speaker verification or voice biometrics
- Deepfake detection or synthetic media analysis
- Self-supervised learning frameworks (e.g., wav2vec, HuBERT)
- Familiarity with edge deployment or real-time inference systems
- Exposure to regulated industries such as healthcare, finance, or government
- Contributions to research publications or open-source projects
Technical Environment
- Programming: Python, PyTorch
- Audio Processing: Librosa, torchaudio
- Cloud Platforms: AWS and/or Google Cloud Platform
- Data pipelines and model serving infrastructure
- Modern MLOps frameworks
What Makes This Opportunity Unique
- Opportunity to work on high-impact AI challenges, including identity verification, fraud detection, and deepfake prevention
- Direct contribution to real-world security and trust systems
- High-visibility role within a collaborative and agile team environment
- Meaningful ownership and influence over core intellectual property and research direction
- Exposure to both advanced research and full-scale production deployment
Salary : $55 - $57