The company is seeking a Machine Learning Engineer to develop innovative solutions for complex problems using cutting-edge machine learning and statistical techniques, specifically focusing on voice and text data for automotive applications.
Requirements
- 3+ years of hands-on experience in Machine Learning in a corporate environment.
- Deep understanding of Voice2Voice Architectures and Speech native models.
- Experience with model quantization techniques and optimization for edge devices.
- Strong experience in audio processing, including feature extraction, noise handling, and acoustic modeling.
- Experience with Tensorflow or PyTorch.
- Experience with speech recognition and text-to-speech technologies.
- Knowledge of multimodal learning and techniques for fusing audio and text information.
Responsibilities
- Design, implement, and optimize an end-to-end Conversational Speech LLM-based virtual assistant.
- Evaluate and benchmark speech native models for in-vehicle applications.
- Design and execute model fine-tuning strategies for automotive domain adaptation.
- Implement tool API frameworks for vehicle system control.
- Implement hardware-specific optimization for Qualcomm SA8255P platform.
- Develop and maintain Python code for audio preprocessing, model integration, and hardware optimization.
- Execute the full modeling lifecycle, including data cleansing, feature creation, and iterative model selection.
Other
- Work in a fast-paced Agile Scrum environment to assist in prototyping, designing, and implementing predictive models and algorithms.
- Document architecture analyses, benchmarking results, and optimization approaches.
- Strong decision-making skills with the ability to analyze data, assess risks, and implement effective solutions.
- Problem-solving skills with the ability to identify challenges, develop creative solutions, and implement effective strategies.
- Proven ability to learn and apply new technologies, programming practices, patterns, and methods.
