Sr Machine Learning Engineer

Role Overview: You will be responsible for developing models to achieve business objectives and tracking their progress with metrics. Your role will involve developing scalable infrastructure for automating training and deployment of ML models, managing resources efficiently to meet deadlines, and creating data visualizations for better data comprehension. Additionally, you will brainstorm and design various POCs using ML/DL/NLP solutions, work with and mentor fellow Data and Software Engineers, and communicate effectively to understand product challenges. Key Responsibilities: - Understand business objectives and develop models to achieve them - Develop scalable infrastructure for automating training and deployment of ML models - Manage resources efficiently to meet deadlines - Create data visualizations for better data comprehension - Brainstorm and design various POCs using ML/DL/NLP solutions - Work with and mentor fellow Data and Software Engineers - Communicate effectively to understand product challenges - Build core Artificial Intelligence and AI services such as Decision Support, Vision, Speech, Text, NLP, NLU, and others - Experiment with ML models in Python using machine learning libraries, Big Data, Hadoop, HBase, Spark, etc. Qualifications Required: - Proficiency in SQL and any NO-SQL database like MongoDB, ElasticSearch - Experience with data visualization tools like Kibana - Expertise in visualizing big datasets and monitoring data - Familiarity with implementing anomaly detection - Proficiency in deep learning frameworks - Proficiency in Python and basic libraries for machine learning - Familiarity with Linux - Ability to select hardware to run an ML model with the required latency - Knowledge of cloud technology like AWS, Google Cloud, or similar technology - Knowledge of Python using machine learning libraries (Pytorch, Tensorflow), Big Data, Hadoop, HBase, Spark, etc. - Deep understanding of data structures, algorithms, and excellent problem-solving skills,