| Machine Learning - New York, New York (Onsite) - Contract at York, New York, USA |
| Email: [email protected] |
| From: Vijay Chepyala, Talent groups [email protected] Reply to: [email protected] Must be local to New York Position: Machine Learning Location:- New York, New York (Onsite) Duration:- Contract POSITION OVERVIEW : As a Machine Learning Engineer responsible for designing and developing machine learning systems, implementing appropriate ML algorithms, conducting experiments, and staying updated with the latest developments in the field. Work with data to create models, perform statistical analysis, and train and retrain systems to optimize performance. Goal is to build efficient self-learning applications and contribute to advancements in artificial intelligence. Responsibilities include: Designing and developing machine learning and deep learning systems Running machine learning tests and experiments Implementing appropriate ML algorithms PREFERRED EXPERIENCE Experience in one or more ML toolkits or Python frameworks Experience and demonstrable knowledge of Deep Learning concepts Understanding of probability and statistics and machine learning concepts such as precision, recall, optimization, hyperparameter tuning, overfitting, and interpretability Experience in applying standard implementations of machine learning algorithms effectively by choosing a suitable model such as decision tree, knn, neural net, or an ensemble of multiple models. Understanding of how components and processes work together and communicate with each other using library calls, REST APIs queueing/messaging systems and database queries. Understanding of system design to avoid bottlenecks and let your algorithms scale well with increasing volumes of data. Self-driven and self-guided in a dynamic environment Experience with PyTorch, NLTK, SciPy, Scikit-Learn, Numpy, OpenCV or equivalent for image preprocessing. Experience with SQL/NoSql databases and queries Familiarity with coding best practices, OOD/OOP, modular design, SOA, and systems architecture Technical skills: Python, pyspark or R programming language for coding Kubernetes and docker for deployment AWS sagemaker or EC2 instances for cloud MYSQL, Oracle, mongodb or Redshift DB for database Python and pyspark for programming Cloudera Distributed Platform for computing & deployment. deep learning/neural networks packages like pytorch, tensorflow in python and use GPU for training distributed computing pyspark and parallel compute in libraries in python Keywords: machine learning database rlang |
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| Tue Jan 23 22:45:00 UTC 2024 |