Fetching information
Preparing content
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work.. Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest. 4+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning). End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark). MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences, related field, or equivalent experience.
This individual will partner closely with senior leadership, product, operations, growth, data engineering and data governance teams to operationalize insights, optimize business performance, and expand CAQH’s capabilities in artificial intelligence (AI), machine learning (ML), and decision science. Work closely with Data Engineering, Architecture, and Governance teams to ensure data science solutions are interoperable, secure, and aligned with CAQH’s enterprise data ecosystem. Proficiency in Python, R, SQL, Spark, and data science frameworks (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost). Familiarity with data governance and compliance frameworks (e.g., HIPAA, HITRUST, GDPR). Bachelor’s degree in computer science, data science, statistics, applied mathematics, or a related field required.
Leverage Azure DevOps for continuous integration and continuous deployment (CI/CD) of ML models. Implement feature flagging to rapidly pilot model enhancements, exception handling, and performance optimization. Proficiency in Python for constructing data pipelines, and using ML frameworks and libraries such as Keras, PyTorch, Scikit-Learn, TensorFlow, and XGBoost. 2+ years of experience developing in a cloud environment (AWS, GCS, Azure)2+ years of experience with Github, Github Actions, CI/CD, and source control. Experience with deep learning, reinforcement learning, NLP, and LLMs is preferred
As an experienced machine learning engineer, you understand good software is more than just a good user experience. 5+ years of experience as a machine learning engineer building production-grade machine learning solutions with a programming language, such as Python, Rust, Go, Scala, or Java. Experience with project work in deep learning, computer vision, NLP, or signal processing. Knowledge of Databricks, PyTorch, Tensorflow, Langchain, or Kubernetes. As part of the application process, you are expected to be on camera during interviews and assessments.
The Applied AI group in Comcast’s Global Entertainment Engineering organization is seeking a passionate and skilled Machine Learning Engineer with expertise in Natural Language Processing (NLP) to join a team of researchers and engineers powering a voice platform used by millions of people every day across the world.. Apply NLP and ML knowledge to analyze and process voice queries using techniques like pattern matching, entity extraction and intent classification.. Proficiency in programming languages like Python, Kotlin and Java, and experience with machine learning frameworks such as TensorFlow, PyTorch and Keras.. Experience with natural language processing, machine learning, deep learning, optimization techniques and evaluation methodologies.. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus.
The goal of a Machine Learning Engineer at Scale is to bring techniques in the fields of computer vision, deep learning and deep reinforcement learning, or natural language processing into a production environment to improve Scale's products and customer experience. Ideally You’d Have: Extensive experience using computer vision, deep learning and deep reinforcement learning, or natural language processing in a production environment. Nice to Haves: Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization. Experience working with cloud technology stack (e.g., AWS or GCP) and developing machine learning models in a cloud environment. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture.
The role will apply statistical programming, modeling, visualization techniques, data mining, and forecasting skills to analyze challenging public sector problems.. Examples will include techniques such as machine learning (ML) supervised and unsupervised learning, regression, neural networks and deep learning, natural language processing, etc.. High degree of experience utilizing SAS, R, or Python to support NLP use cases such as Document Summarization, Named Entity Recognition, Sentiment Analysis, and/or Topic Modeling. At least four years of experience developing scalable, production-ready NLP solutions using sci-kit learn, Keras, TensorFlow, PyTorch, Spark NLP.. Experience leveraging transformer architecture to develop NLP models
Machine Learning Engineer (Contract-to-Hire)Remote (U.S. – NYC Tri-state preferable, Eastern Time Hours Preferred)An innovative software product organization is seeking a Machine Learning Engineer to support the design and deployment of models that power advertising personalization and smarter user segmentation.. Leverage tools such as Google Ad Manager and other ad tech platforms to define, manage, and evaluate user cohorts.. What We’re Looking For:3–5+ years of hands-on experience in machine learning, with a focus on advertising, martech, or audience targeting.. Familiarity with ad tech platforms such as Google Ad Manager (GAM), DV360, or similar tools.. Degree in Computer Science, Statistics, Data Science, or a related field—or equivalent professional experience.
The Antitrust Division of the U.S. Department of Justice (DOJ) is responsible for enforcing federal antitrust laws and promoting fair competition in the marketplace.. Apply natural language processing (NLP), computer vision, or other domain-specific algorithms as required by the research.. Utilize cloud platforms and big data technologies (e.g., AWS, Azure, Hadoop, Spark) for efficient data processing and model deployment.. Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau, Power BI) to present insights effectively.. Strong understanding of big data technologies (e.g., Hadoop, Spark) and cloud platforms (AWS, Azure, Google Cloud).
The Senior AI Data Scientist with the MedStar Health AI Center of AI Excellence drives innovation and transformational change in healthcare by leveraging advanced analytics, artificial intelligence, and machine learning.. As part of the MedStar Health AI Center of Excellence, supports governance efforts by performing and overseeing internal and external model reviews, evaluations and in-vivo monitoring.. Master's degree In computer science, data science, statistics, biomedical informatics, engineering or related technical field.. Expertise in Python, SQL, Scikit-Learn, Spark/Databricks, LangChain and modern cloud MLOps.. Expertise in modern machine learning techniques including decision trees, support vector machines, neural networks as well as natural language processing, embedding and foundation models.
Leidos is looking for an Enterprise Architect to support a large U.S. Department of Justice (DOJ) program.. The Antitrust Division of the U.S. Department of Justice (DOJ) is responsible for enforcing federal antitrust laws and promoting fair competition in the marketplace.. Expertise in AI/ML technologies (e.g., TensorFlow, PyTorch, Scikit-learn, Keras) and understanding of deep learning and natural language processing (NLP).. Strong understanding of big data platforms such as Hadoop, Apache Spark, and data lakes.. Experience with data visualization tools like Power BI, Tableau, or Looker.
We are looking for a machine learning engineer to help develop applied ML models and own end-to-end pipelines that will enable us to deliver real-time insights and guidance to key clients this election cycle.. Our pipeline involves using deep learning to fine-tune large, powerful transformer models, and we are excited to be applying the latest advances in AI tools to our unique, private dataset.. Is a strong Python programmer, and is familiar with standard software development tools and best practices.. Has experience with NLP and training transformer ML models using PyTorch, or similar tools.. Is familiar with cloud services, distributed systems, and other DevOps tools (Docker, Kubernetes, Terraform, etc
We are using our big data coupled with machine learning and AI to help highlight the path forward.. The Data Scientist has applied expertise in Python, distributed databases, advanced AI/ML modeling, statistical analysis, and data visualization at scale.. Employ predictive modeling, natural language processing and categorization techniques to increase and optimize customer experience and revenue generation.. Professional experience with python, including python data libraries (numpy, pandas, matplotlib, scikit-learn) with proven ability to employ python for data manipulation, large-scale analytics, and ensemble-based ML development.. Extensive knowledge, application, and experience in creating and implementing recommendation systems, machine learning, NLP, statistics, and deep learning.
We are looking for an experienced Machine Learning Engineer to join our team on a temporary, 12 month project.. As a Machine Learning Engineer, you will develop and deploy machine learning models for anomaly detection, processing both structured data and unstructured marketing content to identify suspicious behavior patterns and anomalous activities.. Develop NLP pipelines for analyzing ad content and detecting deceptive marketing claims.. Expert proficiency in Python and ML frameworks (scikit-learn, TensorFlow, PyTorch).. Experience with using anomaly detection techniques for fraud detection.
The Antitrust Division of the U.S. Department of Justice (DOJ) is responsible for enforcing federal antitrust laws and promoting fair competition in the marketplace.. Expertise in AI/ML technologies (e.g., TensorFlow, PyTorch, Scikit-learn, Keras) and understanding of deep learning and natural language processing (NLP).. Strong understanding of big data platforms such as Hadoop, Apache Spark, and data lakes.. Experience with data visualization tools like Power BI, Tableau, or Looker.. Certifications: Relevant certifications in enterprise architecture, AI, or data science (e.g., TOGAF, Certified Data Management Professional (CDMP), Microsoft Certified: Azure AI Engineer Associate).
The role will apply statistical programming, modeling, visualization techniques, data mining, and forecasting skills to analyze challenging public sector problems.. Modeling - Select and apply modeling techniques like supervised and unsupervised machine learning, regression, neural networks, and deep learning.. At least four years developing scalable NLP solutions using tools like scikit-learn, Keras, TensorFlow, PyTorch, Spark NLP.. Familiarity with open-source NLP packages such as Gensim, SpaCy, NLTK.. Experience with Databricks and cloud environments, specifically AWS.
The Senior Data Scientist will lead the development of machine learning and deep learning solutions that power intelligent decision-making and innovative products.. Design, build, and evaluate machine learning and deep learning models for classification, regression, recommendation, NLP, computer vision, and time-series forecasting.. 5+ years of industry experience in applied machine learning, with 2+ years focused on deep learning and neural network applications.. Proficiency in Python and ML libraries such as scikit-learn, XGBoost, TensorFlow, Keras, or PyTorch.. Experience with cloud platforms (AWS/GCP/Azure), containerization, and model serving technologies.
Join to apply for the Machine Learning Engineer (TS/SCI) role at Maxar Technologies. Maxar is seeking a talented and driven Machine Learning Engineer to join our innovative team.. Solid understanding of machine learning concepts, algorithms, and libraries (e.g., scikit-learn, TensorFlow, PyTorch).. Experience with natural language processing (NLP), computer vision, or other specialized areas of machine learning.. Sign in to set job alerts for Machine Learning Engineer roles.
Sr. Machine Learning Engineer/Date Scientist (6-Month Project). Join to apply for the Sr. Machine Learning Engineer/Date Scientist (6-Month Project) role at Element. We are looking for an experienced Machine Learning Engineer to join our team on a temporary, 6-month project.. As a Machine Learning Engineer, you will develop and deploy machine learning models for anomaly detection, processing both structured data and unstructured marketing content to identify suspicious behavior patterns and anomalous activities.. Sr Machine Learning Engineer - Fintech Foundation (100% Remote - USA)
Lyric’s solutions leverage the power of machine learning, AI, and predictive analytics to empower health plan payers with pathways to increased accuracy and efficiency, while maximizing value and savings.. Lyric’s strong relationships as a trusted ally to customers resulted in recognition from KLAS as “true partner” and “excellent value for investment,” with a top score for overall customer satisfaction and A+ likelihood to recommend in their October 2023 Payment Integrity and Accuracy Report.. By leveraging advanced coding, analytic reporting, and predictive modeling, the Clinical Data Analyst - Staff uncovers actionable insights that drive innovation and improve outcomes across the organization.. Experience with data in Snowflake on Cloud Platforms. Experience using statistical computer languages (SQL, Python, R) to manipulate data and generate insights from large data sets