Mid-Level Data Research Scientist

Marathon TS is seeking a skilled and motivated Mid-Level Research Scientist to join our team. The ideal candidate will focus on developing and deploying multimodal machine learning models specifically for speaker identification and verification tasks. This role involves designing and refining neural architectures that encompass various features, training and evaluating deep learning models, and enhancing the robustness of these systems for real-world applications in voice authentication and behavioral analysis., * Model Development: Design innovative neural architectures that integrate speech, acoustic, and linguistic features for speaker identification and verification tasks.

• Data Handling: Train deep learning models on large-scale datasets, including participation in the construction and annotation of specialized datasets, such as the “American Dream Dataset “.
• Evaluation & Benchmarking: Benchmark age prediction and speaker verification models, leveraging datasets to enhance model performance and demonstrate superior generalization.
• Research Prototyping: Conduct research initiatives focused on cross-modal representation learning and predictive modeling of political career advancement using voice quality and prosodic features.
• Optimization: Optimize existing models, including the development of lightweight architectures for resource-constrained environments, such as real-time image captioning systems.
• Architecture Design: Evaluate and benchmark diverse adapter architectures for vision-text alignment, while achieving state-of-the-art performance metrics on established datasets (e.g., COCO dataset).
• Collaboration: Collaborate with cross-functional teams to translate research findings into scalable solutions and real-world applications.

• Master’s or PhD in Computer Science, Electrical Engineering, or a related field.
• 3-5 years of experience in machine learning and deep learning, with a proven track record of developing multimodal models.
• Strong proficiency in programming languages such as Python and frameworks including TensorFlow and PyTorch.
• Experience with acoustic and linguistic feature extraction and understanding of speaker identification and verification systems.
• Familiarity with natural language processing (NLP) and computer vision integrations, particularly in real-time applications.
• Strong analytical and problem-solving skills, with the ability to work independently and as part of a team.
• Excellent communication skills to present complex technical concepts to diverse audiences.

Preferred Qualifications:

• Publications in relevant conferences or journals.
• Experience in research involving behavioral analysis and authentication systems
• Understanding of model efficiency and optimization strategies for deploying machine learning models in production.