Job Overview:
We are looking for a skilled Data Scientist with a focus on fine-tuning and training pre-existing machine learning and deep learning models. In this role, you will work with state-of-the-art AI models, adapting them to meet specific business needs, optimizing their performance, and ensuring that they deliver valuable insights and solutions. This position involves leveraging pre-trained models and refining them to perform at their best on company-specific tasks.
Key Responsibilities:
• Model Fine-Tuning: Fine-tune and overtrain pre-existing AI models to improve their performance on specialized tasks or datasets.
• Data Preparation & Preprocessing: Prepare and preprocess data for training, ensuring it is in the appropriate format for model fine-tuning and optimization.
• Model Optimization: Work on hyperparameter tuning, regularization, and other techniques to improve model accuracy and efficiency.
• AI Model Integration: Integrate fine-tuned models into production environments, working closely with software engineers to ensure seamless deployment.
• Evaluation & Testing: Continuously evaluate the performance of fine-tuned models and implement improvements based on key metrics such as accuracy, precision, recall, and F1 score.
• Collaboration: Collaborate with cross-functional teams (engineering, product, etc.) to ensure the AI models meet business objectives and user needs.
• Continuous Learning: Stay up-to-date with the latest advancements in AI, particularly in areas of model fine-tuning and transfer learning, to apply best practices and improve model performance.
• Documentation & Reporting: Provide clear documentation of processes, model configurations, and results, and communicate technical findings to stakeholders in a clear and actionable way.
Required Skills and Qualifications:
Educational Background: Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.
• Experience: Proven experience in working with pre-trained machine learning and deep learning models, fine-tuning, and overtraining them for specific tasks.
• Programming Languages: Proficiency in Python and relevant libraries (e.g., TensorFlow, Keras, PyTorch, Hugging Face Transformers).
• Model Fine-Tuning & Transfer Learning: Strong experience with transfer learning techniques and fine-tuning models for domain-specific applications (voice STT-TTS, NLP, image recognition, etc.).
• Data Handling: Expertise in data preprocessing, feature engineering, and ensuring high-quality input for model training.
• Cloud & Big Data Tools: Familiarity with cloud platforms (AWS, Azure, GCP) and big data technologies is a plus.
• Performance Metrics: Ability to assess and improve model performance using various evaluation metrics and techniques (e.g., cross-validation, grid search).
• Problem-Solving: Ability to troubleshoot and optimize existing models to meet business requirements.
• Communication Skills: Strong verbal and written communication skills to clearly explain the results and potential areas for improvement to non-technical stakeholders.
• Collaboration: Experience working in agile teams and collaborating with engineers, product managers, and other stakeholders.
Preferred Qualifications:
• Experience in fine-tuning models for specific industries (e.g., telecommunication, contact center, finance).
• Familiarity with pre-trained models from sources like Hugging Face, OpenAI, or Google AI.
• Knowledge of reinforcement learning, active learning, or federated learning.
Benefits:
• Competitive salary and performance bonuses.
• Flexible working hours and remote work options.
• Professional development opportunities, including access to cutting-edge AI tools and resources.
• Collaborative and innovative work environment.
