Litmus7 - Artificial Intelligence Engineer - Machine Learning Model

Job Description : - Minimum 3 years of experience in machine learning engineering and AI development - Deep expertise in machine learning algorithms and techniques like supervised/unsupervised learning, deep learning, reinforcement learning, etc. - Solid experience in natural language processing (NLP) - language models, text generation, sentiment analysis, etc. - Proven understanding of generative AI concepts like text/image/audio synthesis, diffusion models, transformers, etc. - Hands-on experience developing and deploying generative AI applications (text generation, conversational AI, image synthesis, etc.) - Experience in MLOps and ML model deployment pipelines. - Proficiency in programming languages like Python, and ML frameworks like TensorFlow, PyTorch, etc. - Knowledge of cloud platforms (AWS, GCP, Azure) and tools for scalable ML solution deployment - Experience with data processing, feature engineering, and model training on large datasets. - Familiarity with responsible AI practices, AI ethics, model governance and risk mitigation - Understanding of software engineering best practices and applying them to ML systems. - Experience with an agile development environment. - Exposure in tools/framework to monitor and analyse ML model performance and data accuracy. - Strong problem-solving, analytical, and communication abilities Responsibilities : - Design, develop and optimize machine learning models for applications across different domains. - Build natural language processing pipelines for tasks like text generation, summarization, translation, etc. - Develop and deploy cutting-edge generative AI models for applications like conversational AI, text/image synthesis, etc. - Implement MLOps practices - model training, evaluation, deployment, monitoring, and maintenance. - Integrate machine learning capabilities into existing products or build new AI-powered applications. - Perform data mining, cleaning, preparation, and augmentation for training robust ML models. - Collaborate with cross-functional teams to translate AI requirements into technical implementations. - Ensure model performance, scalability, reliability. - Continuously research and implement state-of-the-art AI/ML algorithms and techniques. - Manage the end-to-end ML lifecycle from data processing to production deployment (ref:hirist.tech)

Location: in, IN

Posted Date: 11/3/2024