Machine learning solutions developer

Role Overview: As a Senior AI/ML Data Scientist, your main responsibility will be to develop, deploy, and maintain AI/ML models using Python and Django. You will be required to build scalable data pipelines and APIs by integrating ML models into production. Additionally, you will work across domains such as NLP, Computer Vision, and Generative AI for real-world solutions. Your role will also involve performing data preprocessing, model training, and performance tuning. Collaboration with cross-functional teams for AI product development and insights will be crucial. You will be expected to automate workflows and ensure robust, reproducible, and efficient ML systems. Implementation of MLOps practices such as Docker, MLflow, Kubernetes, and Azure will also fall under your responsibilities. Key Responsibilities: - Develop, deploy, and maintain AI/ML models using Python and Django. - Build scalable data pipelines and APIs integrating ML models into production. - Work across domains such as NLP, Computer Vision, and Generative AI for real-world solutions. - Perform data preprocessing, model training, and performance tuning. - Collaborate with cross-functional teams for AI product development and insights. - Automate workflows and ensure robust, reproducible, and efficient ML systems. - Implement MLOps practices (Docker, MLflow, Kubernetes, Azure). Qualification Required: - Bachelor's/Master's in CS, Data Science, or related field. - 5-6 years of experience in AI/ML & Data Science. - Strong proficiency in Python, PyTorch, TensorFlow, Scikit-learn, and Hugging Face. - Hands-on experience with LLMs, embeddings, vector DBs, and RAG. - Experience in recommendation, personalization, and predictive modeling. - Skilled in SQL/NoSQL, data pipelines, and APIs (Quick API, Django REST, Flask). - Familiarity with Cloud ML deployments (Azure/AWS/GCP). - Knowledge of Docker, Kubernetes, Git, and CI/CD. (Note: No additional details about the company were provided in the job description) Role Overview: As a Senior AI/ML Data Scientist, your main responsibility will be to develop, deploy, and maintain AI/ML models using Python and Django. You will be required to build scalable data pipelines and APIs by integrating ML models into production. Additionally, you will work across domains such as NLP, Computer Vision, and Generative AI for real-world solutions. Your role will also involve performing data preprocessing, model training, and performance tuning. Collaboration with cross-functional teams for AI product development and insights will be crucial. You will be expected to automate workflows and ensure robust, reproducible, and efficient ML systems. Implementation of MLOps practices such as Docker, MLflow, Kubernetes, and Azure will also fall under your responsibilities. Key Responsibilities: - Develop, deploy, and maintain AI/ML models using Python and Django. - Build scalable data pipelines and APIs integrating ML models into production. - Work across domains such as NLP, Computer Vision, and Generative AI for real-world solutions. - Perform data preprocessing, model training, and performance tuning. - Collaborate with cross-functional teams for AI product development and insights. - Automate workflows and ensure robust, reproducible, and efficient ML systems. - Implement MLOps practices (Docker, MLflow, Kubernetes, Azure). Qualification Required: - Bachelor's/Master's in CS, Data Science, or related field. - 5-6 years of experience in AI/ML & Data Science. - Strong proficiency in Python, PyTorch, TensorFlow, Scikit-learn, and Hugging Face. - Hands-on experience with LLMs, embeddings, vector DBs, and RAG. - Experience in recommendation, personalization, and predictive modeling. - Skilled in SQL/NoSQL, data pipelines, and APIs (Quick API, Django REST, Flask). - Familiarity with Cloud ML deployments (Azure/AWS/GCP). - Knowledge of Docker, Kubernetes, Git, and CI/CD. (Note: No additional details about the company were provided in the job description)