ML/AI Engineer

Role: As a Senior Machine Learning Engineer, you will develop cutting-edge algorithms for consumer product development. You will work with design and engineering teams to create intelligent workflows on the 9series platform. Ultimately, you will drive the innovations that benefit millions of people's lives. Responsibilities: Build and maintain the infrastructure for data and model management Work closely with the 9series design and engineering teams for machine learning-adjacent components, such as visualisation, ad-hoc data analysis, and data processing To research, modify, and apply data science and data analytics prototypes. To create and construct methods and plans for machine learning Employing test findings to do statistical analysis and improve models To search the internet for training datasets that are readily available ML systems and models should be trained and retrained as necessary To improve and broaden current ML frameworks and libraries To create machine learning applications in accordance with client or customer needs To investigate, test, and put into practice appropriate ML tools and algorithms. To evaluate the application cases and problem-solving potential of ML algorithms and rank them according to success likelihood To better comprehend data through exploration and visualisation, as well as to spot discrepancies in data distribution that might affect a model's effectiveness when used in practical situations Skills: Data Modelling Natural Language Processing - Word2vec, Sentiment Analysis, Summarization, Gensim, and NLTK Unix & Linux Servers Programming Languages - C, C++, Python and Java Spark and Hadoop Excellent programming and algorithmic skills - Are proficient with Python and experience with data processing tools (e.g., SciPy, NumPy, Pandas, PyTorch, and Apache Spark) Have an in-depth understanding of supervised and unsupervised machine learning algorithms. Knowledge of engineering causal models and convolutional neural networks a big plus Have a proven track record of deploying learning algorithms in a production system Have demonstrated end-to-end ownership of projects - Have stellar listening and explanation skills. Requirements: Have 4+ years of professional experience in machine learning or quantitative analysis or have a Ph.D. in Computer Science, Statistics, Mathematics, or Physics Advanced maths and statistics knowledge, particularly in the areas of calculus, linear algebra, and Bayesian statistics Advanced degree in maths, computer science, statistics or a related field A master's degree in artificial intelligence, deep learning, or a related discipline Strong teamwork, problem-solving, and analytical skills. Abilities in software engineering Knowledge of data science Languages for coding and programming, such as Python, Java, C++, C, R, and JavaScript Practical understanding of ML frameworks Practical familiarity with ML libraries and packages Recognize software architecture, data modelling, and data structures Understanding of computer architecture