Machine Learning (ML)
Data Science1 Job Title: Senior Data Scientist
Location: Bangalore
Employment Type: Full-Time
We are seeking a highly skilled and experienced Senior Data Scientist to join our team. In this role, you will leverage advanced Natural Language Processing (NLP), Deep Learning, and traditional Machine Learning (ML) techniques to build and optimize our NLP-driven products and services. You will work closely with cross-functional teams to develop scalable, highperformance NLP models that solve complex language and data-related challenges. If you are passionate about advancing language understanding and have hands-on experience with the latest NLP frameworks, models, and techniques, we would love to speak with you!
Responsibilities
• Model Development and Optimization: Design, build, and deploy NLP models, including transformer models (e.g., BERT, GPT, T5) and other SOTA architectures, as well as traditional machine learning algorithms (e.g., SVMs, Logistic Regression) for specific applications.
• Data Processing and Feature Engineering: Develop robust pipelines for text preprocessing, feature extraction, and data augmentation for structured and unstructured data.
• Model Fine-Tuning and Transfer Learning: Fine-tune large language models for specific applications, leveraging transfer learning techniques, domain adaptation, and a mix of deep learning and traditional ML models.
• Performance Optimization: Optimize model performance for scalability and latency, applying techniques such as quantization, ONNX formats etc.
• Research and Innovation: Stay updated with the latest research in NLP, Deep Learning, and Generative AI, applying innovative solutions and techniques (e.g., RAG applications, Prompt engineering, Self-supervised learning).
• Stakeholder Communication: Collaborate with stakeholders to gather requirements, conduct due diligence, and communicate project updates effectively, ensuring alignment between technical solutions and business goals.
• Evaluation and Testing: Establish metrics, benchmarks, and methodologies for model evaluation, including cross-validation, and error analysis, ensuring models meet accuracy, fairness, and reliability standards.
• Deployment and Monitoring: Oversee the deployment of NLP models in production, ensuring seamless integration, model monitoring, and retraining processes.
Technical Skills
• Advanced NLP Techniques: Proficiency in transformer models (e.g., BERT, RoBERTa, GPT, T5), and experience with techniques like entity recognition (NER), text classification, summarization, question answering, and language generation.
• Programming: Strong programming skills in Python, with experience in NLP libraries such as Hugging Face Transformers, spaCy, NLTK, and Gensim.
• ML and DL Frameworks: Proficiency in ML and Deep Learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Traditional ML Techniques: Familiarity with traditional ML models like SVMs, Logistic Regression, Decision Trees, and KNN etc
• Evaluation Metrics: Familiarity with NLP and ML evaluation metrics (e.g., BLEU, ROUGE, F1, accuracy, precision, recall) and experience designing experiments and tests
Subodh Popalwar
Software Engineer, Memorres
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Software Engineer, Memorres