AIML Engineer

Job Description

Education: Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related certifications or experience in NLP & CV. Years of Experience: Minimum 2 years of experience in Deep Learning, NLP,CV, MLOps and its related technologies. Responsibilities: - Design, develop, and deploy state-of-the-art NLP and CV models and algorithm - Collaborate with cross-functional teams to understand requirements and develop customised NLP & CV solutions and have experience in building the python backend using Flask / Django. - Database integration preferably using MongoDB or any other vector databases. - Maintain and improve the performance, accuracy, and efficiency of existing AI/ML models and their deployment on Cloud platforms (AWS) and monitor their performance using MLOps tools such as MLFlow, DVC. - Experience in building End to End data pipelines - Stay updated with emerging AI/ML technologies, LLMs ,RAG - Conduct regular performance evaluations of AI/ML models using production grade MLOps solutions. - Troubleshoot and resolve any issues arising from the implementation of NLP & CV models. - Develop and monitor the code that runs in production environments using MLOps practices. Requirements: - Strong experience with Deep learning and NLP frameworks such as TensorFlow or other open-source machine learning frameworks. - Experience of using both tensorflow and pytorch frameworks - Proficient in programming languages, such as Python or Java, and experience with AI/ML libraries. - Familiarity with the integration of APIs, such as REST API, OpenAI API, for implementing advanced AI-driven features. - Solid understanding of Machine learning and Deep learning algorithms, concepts, and best practices in a production environment using MLOps. - Experience with big data technologies, such as Hadoop and Spark, is a plus. - Strong problem-solving skills. - Excellent communication and teamwork skills, with the ability to collaborate effectively with team members from various disciplines. - Eagerness to learn and adapt to new technologies and industry trends.