AI/ML Engineer and Developer

As an AI/ML Engineer at EpixelSoft, you will be responsible for designing, developing, and implementing machine learning models to enhance services, focusing on AI-driven solutions in healthcare, fintech, and enterprise software domains. You will collaborate with cross-functional teams to deploy these models into production environments and ensure they meet business requirements and performance standards. Key Responsibilities: - Design, develop, and deploy machine learning models, emphasizing generative AI, deep learning, and large language models (LLMs). - Develop end-to-end machine learning pipelines integrating with backend services, data sources, and third-party APIs. - Implement deployment processes for AI models, including monitoring, optimization, and retraining strategies. - Continuously improve efficiency and scalability of machine learning algorithms and workflows. - Collaborate with data scientists, software engineers, and product managers to integrate AI solutions into business applications. - Implement and maintain CI/CD pipelines for machine learning models. - Oversee infrastructure for model training and deployment, optimizing cloud service and computational resources. - Build and integrate REST APIs for consumption of machine learning models. - Maintain documentation of processes, models, and code. - Stay updated with AI/ML trends to enhance EpixelSoft's offerings. Required Qualifications: - Bachelors or Masters degree in Computer Science, Data Science, Engineering, or related field. - Minimum 3 years of hands-on experience in AI/ML model development, deployment, and optimization. - Proficiency in TensorFlow, PyTorch, Keras, Pandas, NumPy, Scikit-learn. - Expertise in Python, JavaScript (React.js/Node.js). - Understanding of AI model deployment, containerization (Docker), orchestration (Kubernetes), cloud platforms (AWS, Azure, GCP). - Experience with version control (Git), CI/CD pipelines, and model lifecycle management. - Familiarity with large-scale datasets, data preprocessing, feature engineering, data wrangling. - Experience with SQL, NoSQL databases (PostgreSQL, MongoDB), data storage solutions. - Ability to work in cross-functional teams and communicate technical concepts effectively. - Knowledge of AI/ML tools for monitoring, testing, and retraining models. Preferred Qualifications: - Experience with deep learning frameworks, natural language processing (NLP). - Familiarity with MLOps tools like Azure ML, MLFlow, Databricks, Kubeflow. - Prior experience deploying AI solutions in healthcare, fintech, or enterprise environments. - Knowledge of RESTful API development and integration.,