Ivy Mobility - Senior AI/ML Engineer

Position : Lead AI/ML EngineerQualifications : - Overall 8+ years of work experience as a Machine Learning Engineer or related role, with min. 3+ years as a team lead.- Strong coding experience in Python is required.- More than 4+ years of experience with designing and developing popular, highly scalable, distributed ML models and open-source projects.- Contribution towards multiple use cases.- Understanding of data structures, data modelling and software architecture.- Familiarity and proficiency with machine learning frameworks (like PyTorch, TensorFlow, Keras, MxNet) and libraries (like scikit-learn, pandas).- Knowledge of CUDA, OpenCL.- Understanding and scripting on SQL/ NoSQL databases (e.g., MySQL, MangoDB).- Familiarity with various operating systems (e.g., Windows, UNIX/Linux, Ubuntu).- Knowledge in other programming languages like Java, .net, JavaScript is an added advantage.- Knowledge on deployment of the ML models on any cloud-based platforms (AWS, Azure, GCP).- Knowledge on Big Data & tools like Spark based distributed training and inferencing.- Reinforcement Learning, Neural Networks and Natural Language Processing knowledge on packages like NLTK, Gensim, SpaCy, CoreNLP is a bonus.- Knowledge of text detection, generative models, reinforcement learning, model compression / optimization.- Deep and profound knowledge of math, probability, statistics, and algorithms.- Should have led a team of engineers towards deployment of projects.- Outstanding analytical and problem-solving skills.- Good team player and excellent written and verbal technical communication skills.- Preferable to have FMCG/CPG domain knowledge.- BE / BCA / BSc in Computer Science; Masters degree in the same stream is a plus.Responsibilities : - Deliver robust, well-tested, and fully documented modules to serve the use cases.- Collaborate with Product Management and proactively provide inputs during new use case/feature/module development or connects with project teams.- Act as an anchor to lead the developments from technical front.- Design and work with engineering team to implement the entire application modules as discoverable microservices, experience hosting and deploying ML solutions.- Collaborate with Product teams, system architects, designers, and engineers to support the development of robust machine learning systems.- Continuously improve the efficiency, robustness, and cost of existing modules.- Assess and recommend technology choices and directions in consideration of cost-benefit trade-offs.- Build engineering plans, and schedule estimates.- Perform code reviews and ensure proper design and delivery.- Promote best practices and establishing team processes.- Identify infrastructure and architectural investment needs.- Hire, develop, and lead an inclusive, engaged, and high performing team. (ref:hirist.tech)