Lead ML / Data Scientist

As a Machine Learning Engineer at SoftTech Engineers Limited (SEL), you will be involved in designing and developing end-to-end Generative AI and interpretable AI/ML solutions. Your main responsibilities will include: - Hands-on experience with Python-based web and back-end frameworks such as Django and Flask. - Hands-on experience with Generative AI across various Large Language Models (LLMs) like OpenAI, Gemini, Mistral, Falcon, etc. - LLM Fine-tuning experience with techniques like PEFT, LoRA, QLoRA, Adapters, etc. - Proficiency in NLP, Sentiment Analysis, Topic Modelling, Seq2Seq, Attention model, Tokenizer, TFIDF, Word2Vec, etc. - Familiarity with Python libraries and tools including Pytorch, Keras, TensorFlow, OpenCV, Spacy, Scikit-learn, Pandas, Git, SQL, Databricks, R, etc. - Expertise in database management with both SQL and NoSQL databases. Additionally, you will be expected to: - Implement various machine learning techniques such as Neural Networks, Deep Learning algorithms (CNN/RNN/LSTM), Predictive modeling, Exploratory Data analysis, Linear Regression, Logistic Regression, Clustering Techniques, Nave Bayes, Ensemble methods, Gradient Boosting, XGBoost, Support Vector Machine (SVM), Decision Tree, Random forest, Knowledge Graphs, etc. - Conduct quick Proof of Concepts (POCs) and build Minimum Viable Products (MVPs) to demonstrate solution possibilities across different domains. - Ensure efficient utilization of tools and processes for effective delivery. - Build SOLID solutions with purposeful development patterns on Azure cloud platforms. Qualifications required for this role include a B.Tech/M.Tech degree with relevant experience in Machine Learning and AI technologies. As a Machine Learning Engineer at SoftTech Engineers Limited (SEL), you will be involved in designing and developing end-to-end Generative AI and interpretable AI/ML solutions. Your main responsibilities will include: - Hands-on experience with Python-based web and back-end frameworks such as Django and Flask. - Hands-on experience with Generative AI across various Large Language Models (LLMs) like OpenAI, Gemini, Mistral, Falcon, etc. - LLM Fine-tuning experience with techniques like PEFT, LoRA, QLoRA, Adapters, etc. - Proficiency in NLP, Sentiment Analysis, Topic Modelling, Seq2Seq, Attention model, Tokenizer, TFIDF, Word2Vec, etc. - Familiarity with Python libraries and tools including Pytorch, Keras, TensorFlow, OpenCV, Spacy, Scikit-learn, Pandas, Git, SQL, Databricks, R, etc. - Expertise in database management with both SQL and NoSQL databases. Additionally, you will be expected to: - Implement various machine learning techniques such as Neural Networks, Deep Learning algorithms (CNN/RNN/LSTM), Predictive modeling, Exploratory Data analysis, Linear Regression, Logistic Regression, Clustering Techniques, Nave Bayes, Ensemble methods, Gradient Boosting, XGBoost, Support Vector Machine (SVM), Decision Tree, Random forest, Knowledge Graphs, etc. - Conduct quick Proof of Concepts (POCs) and build Minimum Viable Products (MVPs) to demonstrate solution possibilities across different domains. - Ensure efficient utilization of tools and processes for effective delivery. - Build SOLID solutions with purposeful development patterns on Azure cloud platforms. Qualifications required for this role include a B.Tech/M.Tech degree with relevant experience in Machine Learning and AI technologies.