Seisei.ai Hiring Machine Learning Engineer Job - Remote Freshers Can apply
Job Title: Machine Learning Engineer Job
Company: Seisei.ai
Location: Remote
Eligibility: freshers / Experience
Requirements
- Strong programming skills in Python and experience with deep learning libraries, preferably PyTorch.
- Familiarity with machine learning concepts, techniques, and best practices.
- Solid understanding of neural networks and deep learning architectures.
- Prior experience with audio processing or computer vision is a plus.
- Good problem-solving and critical-thinking abilities.
- Strong communication and teamwork skills.
- A strong desire to learn and contribute to cutting-edge machine learning research.
Responsibilities
- What will be the responsibilities of the employee
- Develop Audio-Driven Lip Sync Models: Collaborate with the team to design and implement deep learning models for audio-driven lip synchronization. You will be responsible for researching and implementing state-of-the-art techniques to achieve realistic and accurate lip sync.
- Fine-Tuning Deep Learning Models: Work on fine-tuning existing deep learning models to improve their performance on specific tasks. This may involve data augmentation, hyperparameter tuning, and model architecture adjustments.
- Data Preprocessing and Analysis: Prepare and preprocess audio and video data for model training. Conduct data analysis to identify patterns and insights that can improve model performance.
- Experimentation and Evaluation: Conduct experiments to evaluate the performance of different models and algorithms. Use relevant metrics to assess the quality of lip sync generated by the models.
- Documentation: Maintain detailed work documentation, including code, experiments, and findings. This documentation will be essential for knowledge sharing and future reference.
- Collaboration: Collaborate with team members on various aspects of the project, including regular meetings to discuss progress, challenges, and potential improvements
Hiring Process
- Resume Shortlisting
- Technical interview(1-2 rounds)
- HR round
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