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Expert level of Advanced and Predictive Analytical Methods e.g., Simulation, Design of Experiments, Genetic Algorithms, Ensemble Methods, Naïve Bayes, Neural Networks, regression, image processing, natural language processing.
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2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning and/or natural language processing. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day.
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Experience in Natural language processing (NLP), Prompt engineering, Embedding, Vector DB. Experience in the Design and implementation of AI/ML models and solutions using Google Cloud Platform technologies, including but not limited to Vertex AI , BigQuery, AI Platform, TensorFlow Extended (TFX), Dataflow, and Compute Engine.
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Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow. Experience with building and training machine learning models using tools like TensorFlow, Keras, or PyTorch.
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Curate and deploy centralized versions of state-of-the-art foundational models and specialized models in specific domain areas, such as DoD lexicon-specific Natural Language Processing (NLP) models.
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In this role, you'll be collaborating closely with the most advanced ML teams worldwide, tackling some of the most challenging ML issues in areas like computer vision, robotics, natural language processing, and beyond.
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AWS,Azure,Data Analytics,Data Engineering,Data science techniques,Deep Learning,Effective communication skills,Google Cloud Platform (GCP),HuggingFace,Machine learning techniques,Natural Language Processing (NLP),PyTorch,Scikit-learn,TensorFlow.
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Familiarity with the OpenAI API and its capabilities for natural language processing (NLP) and generative modeling is highly desirable. Strong knowledge of Python libraries and frameworks relevant to data science and AI (e.g., pandas, NumPy, scikit-learn, TensorFlow, PyTorch, spaCy) rather than general frameworks like anaconda which is a distribution.
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Understanding of natural language processing (NLP), computer vision, and other AI/ML subfields. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch). At least one implementation of using Large Language Models (LlaMa2) with a GPU based infrastructure.
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Ability to design and implement end-to-end machine learning pipelines for data ingestion, processing, modeling, and deployment. Familiarity with cloud-based data storage and processing technologies for handling large datasets efficiently.
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Previous experience in deep learning projects, such as computer vision or natural language processing. Environment Setup: Set up and maintain deep learning environments using frameworks like TensorFlow, PyTorch, or Keras.
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Documented experience with the infrastructure required for the development and implementation of Large Language Models (LLMs), Natural Language Processing (NLP), Computer Vision, Image Processing, and various generative AI techniques.
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We are doing world-class work in machine learning, computer vision, natural language processing, speech and audio, and knowledge, and transferring our work into products, which hundreds of millions of users worldwide use.
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We are looking for a passionate, talented Senior Applied Scientist in the field of Natural Language Processing (NLP), Computer Vision (CV), Ads Recommender Systems, and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware Brand Understanding.
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Proficiency in AI and machine learning technologies, including deep learning, reinforcement learning, natural language processing, and computer vision. Expertise in popular AI frameworks and libraries, such as TensorFlow, PyTorch, or scikit-learn.
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