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Data science, machine learning, optimization models, Master's degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Strong hands-on skills in sourcing, cleaning, manipulating, and analyzing large volumes of data using distributed computing platform and visualization tools (Python, R, SQL, Spark, Hive, Tableau etc. Experienced with traditional as well as modern machine learning and statistical techniques, including A/B testing, Causal Inference, Regression, Classification, Ensemble Methods, Deep Learning, Natural Language Processing, and Reinforcement Learning.
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Tool Familiarity : Experience with tools and frameworks popular in the LLM and NLP communities, such as LangChain, LlamaIndex, PyTorch, and TensorFlow. Tool Familiarity : Experience with tools and frameworks popular in the LLM and NLP communities, such as LangChain, LlamaIndex, PyTorch, and TensorFlow.
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Experience in developing or using deep learning frameworks (e.g. Tensorflow, Keras, Caffe, PyTorch, ONNX, etc.) XLA, TVM, MLIR, LLVM, OpenAI Triton, deep learning models and algorithms, and LLM designs Strong communication and interpersonal skills along with the ability to work in a dynamic and high distributed team Comfortable working across highly matrixed organizations and navigating cross functional relationships and conflicting priority and challenges.
Full-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Apply supervised and unsupervised learning techniques, such as regression, decision trees, random forests, gradient boosted decision trees (XGBoost, LightGBM), KNN, and t-SNE- Develop and optimize deep learning models using tools such as TensorFlow, Keras, PyTorch, or MXNet- Explore and integrate generative AI technologies such as OpenAI, Llama 2, LangChain, LlamaIndex, vector databases, and RAG applications.
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Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch). Proficient in Python/R, PyTorch/TensorFlow, SQL, Big Data and cloud technologies.
ExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Preferred skills: NLP, Text mining, Tableau, PowerBI, SAS, Tensorflow. Preferred skills: NLP, Text mining, Tableau, PowerBI, SAS, Tensorflow. Spring boot, Microservices, Docker, Jenkins and REST API's experience.
RemoteExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Familiar with deep learning platforms (e.g., Keras, Tensorflow) and related classification and segmentation algorithms. Our areas of expertise include remote sensing, geospatial analysis, GIS, soil science, water quality and demand evaluation, agricultural systems, salinity and nutrient management, ecosystem restoration, statistics, and regulatory policy.
RemoteExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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Expertise in machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and programming languages (e.g., Python, Java). Expertise in machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and programming languages (e.g., Python, Java.
Full-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Deep knowledge of Data Science and related technologies (Python, R, scikit-learn, Tensorflow, PyTorch, etc.) Experience with cloud data warehouses (Snowflake, AWS Redshift, Google BigQuery, Azure Data Warehouse, Databricks Lakehouse, etc.
$106,300 - $235,400 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Experience with deep learning frameworks (e.g., TensorFlow, PyTorch). Understanding of natural language processing (NLP), computer vision, and other AI/ML subfields. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch.
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Hands-on experience in machine learning techniques, NLP algorithms and Optical Character Recognition (OCR). CGI is seeking a Technical Lead for Artificial Intelligence and Machine Learning. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for deploying and scaling AI systems.
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ML Libraries / Frameworks - NumPy / Matplotlib / Pandas / Scikit-Learn / PyTorch / TensorFlow / Shogun, etc. Technical Environment: AWS (Lambda / EBS / EC2 / S3 / Security / CloudFormation / CloudWatch / Terraform / IaC), Azure (DevOps / CI/CD / DataFactory), and PowerBI.
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Proficiency with common ML tools (e.g., Spark, TensorFlow, PyTorch) 4 years experience as an Machine Learning Engineer, Applied Scientist, or similar role. As a Senior Machine Learning Engineer II, you will be responsible for developing ML solutions to increase the safety, efficiency and sustainability of the physical operations.
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Data Science knowledge and familiarity with Client libraries such as Pandas, Scikit, TensorFlow, xgboost, time series frameworks like prophet/or equivalent frameworks. In-depth understanding of Google Cloud ecosystem for Data Engineering & MLOps - cloud composer, dataproc, dataproc serverless, big query, cloudrun, vertex, vertex pipelines, GKE.
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tensorflow job in Dallas, TX
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