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The Senior Data Scientist designs, develops, and implements advanced data science models for priority business use cases across the enterprise.. Define batch or real-time streaming data needs, evaluate data quality, and extract/manipulate data in a "Big Data" environment.. Analytical Skills: Strong understanding of core analytical and statistical methods, including regression, segmentation/clustering, predictive modeling, time-series analysis, and machine learning techniques.. Data scientist fluent in complex algorithms and analytics methodologies across multiple platforms and languages, including Google Cloud Platform.. Understanding of core analytical and statistical methods, including regression, segmentation/clustering, predictive modeling, time-series analysis, and machine learning techniques.
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.. Extensive experience using computer vision, deep learning and deep reinforcement Learning, or natural language processing in a production environment. Strong programing skills in Python or Javascript, experience in Tensorflow or PyTorch. Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization. AWS or GCP) and developing machine learning models in a cloud environment
We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society.. We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments.. BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.. or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.. Deep understanding of state-of-the-art machine learning techniques and models.
Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. 7+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role.. Data Engineering technologies (Ex: Spark, Hadoop, Kafka).. Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow).. More than 10,000 organizations worldwide including Comcast, Cond Nast, Grammarly, and over 50% of the Fortune 500 rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.
data using SQL and NoSQL databases, R, Python or other appropriate languages to enable analysis, model development, and solution deployment. moderate to complex data science, machine learning, traditional artificial intelligence, generative artificial intelligence or optimization projects, working with stakeholders to understand contextual problems quickly and define, analyze, and deliver solutions based on business objectives.. Proficiency in programming languages such as Python, R, SQL, and familiarity with Java or Scala.. Previous hands-on experience with AI/Machine Learning frameworks and tools like TensorFlow, PyTorch, or scikit-learn. Family benefits includingparental, pediatric and family building support, adoption and surrogacy reimbursement, and dependent care spending account (with employer match).
Master's or PhD in Electrical or Computer Engineering, Statistics, Mathematics, or Data Science domains.. Proficiency in programming languages such as Python, R, or Java. Experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn.. Experience with cloud platforms such as AWS, Azure, or Google Cloud.. Familiarity with big data technologies like Hadoop, Spark, or Kafka.
Nooks is the AI Sales Assistant Platform (ASAP) that automates the busywork so reps can focus on the human part of selling and generate more sales pipeline. Our approach involves LLM embeddings, few-shot learning, data labeling, and continuous monitoring of model performance in prod. Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field. Full stack ML Eng chops: proficiency in general purposes programming languages such as Python/Javascript, and with libraries like TensorFlow, PyTorch, Keras, scikit-learn etc. Expertise in areas like NLP, Deep Learning, Anomaly Detection, Transformers and Large Language Models.
5+ years of experience machine learning, AI or data science preferably in the banking or Finance sector. Strong Programming skills in Python, R or Scala with expertise in ML Libraries, such as TensorFlow, Pytorch, Scikit-learn. Experience in big data tech (Hadoop, Spark) SQL or No SQL database. Hands on experience with ML ops tools (Docker, Kubernetes, MLflow, Kubeflow, Airflow). Talent Acquisition Group – Strategic Recruitment Manager
Master's degree, or foreign educational equivalent, in Computer Science, Mathematics, Physics, Applied Science, or a related STEM field, plus 2 years of post-baccalaureate experience in job offered or any Machine Learning/engineering related job titles.. 2 years of experience in data analytics, developing Machine Learning (ML) algorithms, optimization methods, and Deep Learning (DL) and Neural network libraries to optimize neural networks and train and evaluate different models.. 2 years of experience in Natural Language Processing, Computer Vision Technologies, Reinforcement learning, and semi-supervised learning.. 2 years of experience in data science development tools and languages including R, Python, Java, TensorFlow, PyTorch, Flask.. 2 years of experience in developing technologies for inference, predictive modeling, general-purpose data-driven modeling, and optimization of systems.
As an AI Engineer, you will be responsible for designing, developing, and deploying cutting-edge artificial intelligence and machine learning models to address complex challenges and enhance the capabilities of our products and services.. AI Model Development: Design, develop, and deploy machine learning and deep learning models for various applications, such as natural language processing (NLP), computer vision, and predictive analytics.. Proven experience (2+ years) working with machine learning, deep learning, or AI technologies.. Familiarity with a wide range of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Keras, Scikit-learn, etc. Experience with cloud platforms (AWS, Azure, Google Cloud) for deploying AI models is preferred.
The Sr. Software Engineer Machine Learning and Artificial Intelligence plays a crucial role in developing AI-driven solutions that enhance patient care, streamline operations, and improve clinical decision-making.. This position requires expertise in machine learning, deep learning, software engineering, and healthcare data management with emphasis on platform architecture.. Implement natural language processing (NLP) models for extracting insights from clinical notes, electronic health records (EHRs), and medical literature.. Experience with natural language processing (NLP) and computer vision for healthcare applications.. Experience working with data warehouse solutions such as Snowflake, Data Lake, or Oracle ADB.
Leverage your deep knowledge of artificial intelligence (AI) principles, including machine learning, natural language processing, computer vision, and reinforcement learning.. Show strong programming skills in languages like Python, along with proficiency in deep learning frameworks such as TensorFlow, PyTorch, or similar.. 2+ years of combined academic and industrial research experience in machine learning, NLP, information retrieval, deep learning or a related field.. Experience in machine learning systems (e.g. SageMaker, MLFlow), and deep learning frameworks (e.g. TensorFlow, PyTorch, MXNet etc). Preference for a publication record in top-tier ML and NLP conferences (e.g. NeurIPS, ICML, SIGIR, ICLR, ACL, EMNLP, etc.)
Machine Learning Model Development: Design, develop, and train machine learning models using a variety of algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.. Required Experience/Knowledge, Skills & Abilities: 3+ years' work experience as a data scientist preferably in healthcare environment but candidates with suitable experience in other industries will be considered Knowledge of big data technologies (e.g., Hadoop, Spark Technical Proficiency: Strong programming skills in languages such as Python and R, and experience with machine learning frameworks like TensorFlow, Keras, or PyTorch.. Data Visualization: Proficiency in data visualization tools (e.g., Tableau, Power BI) to present complex data insights effectively.. Preferred Experience: Experience with cloud platforms (e.g., Databricks, Snowflake, Azure AI Studio etc.). Familiarity with natural language processing (NLP) and computer vision techniques.
Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows.. 7+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role. Expertise in one of the following:Data Engineering technologies (Ex: Spark, Hadoop, Kafka)Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow). More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.. Enterprise Architect / Solution Executive (Large Deals) - US RemoteSr. Cloud and Guidewire Architect - Hybrid or Remote Opportunity
Data Analysis: Perform exploratory data analysis (EDA) on semiconductor manufacturing data, including wafer fabrication, yield, and defect rates.. Tools and technologies: Docker, Containerization, Kubernetes, Jenkins, Ansible, Elasticsearch, SSL, Microservices, data visualization tools (e.g., Streamlit, Tableau, PowerBI, etc. Frontend languages, frameworks/libraries, and packaging: HTML, CSS, JavaScript, Typescript, Angular, HighCharts, Plotly, AG Grid, BootStrap, Ngx Bootstrap, RxJS, npm, Jenkins.. Backend/API languages, frameworks, and databases: Knowledgeable in Python, Flask, and FastAPI. Experience with RESTful APIs and minor experience with WSLs. Experience with MySQL, MSSQL, Oracle, PostgreSQL, MongoDB, Neo4j, BigQuery SQL, Snowflake SQL, and a basic understanding of SSL. Experience in Git and Bitbucket tools.. Hands-on experience with Linux OS, RPi, Odroids (Embedded systems).
Our client is at the forefront of artificial intelligence, leveraging cutting-edge data science and machine learning to solve complex challenges.. Our client is seeking a Python Developer to develop and optimize applications that support machine learning and data science initiatives.. Develop predictive analytics and deep learning solutions to enhance business intelligence and decision-making.. Strong understanding of predictive analytics, deep learning, and AI model development.. Hands-on experience with big data processing technologies, including Spark, Hadoop, or Databricks.
As the nation’s largest senior care advisory service, A Place for Mom helps hundreds of thousands of families every year navigate the complexities of finding the right senior care solution for their loved ones across home care, independent living, memory care, assisted living, and more. A Place for Mom is looking for a Staff Machine Learning Engineer to help build practical, data-driven machine learning applications focused in the Engineering space. This position reports to the VP of Engineering and works directly in the Engineering organization while also working closely with the Data Science team which includes data scientists and machine learning engineers. Deep understanding of real-time inference systems, streaming data pipelines, model serving services, feature store monitoring and latency optimization for ML & LLM applicationsSolve complex problems with multilayered data sets and optimize existing machine learning libraries and frameworks. Technical Skills: Expertise in SQL, Databricks, AWS services, Python, Spark and machine learning frameworks such as XGBoost, Scikit, TensorFlow, Keras or PyTorch.
As the nation’s largest senior care advisory service, A Place for Mom helps hundreds of thousands of families every year navigate the complexities of finding the right senior care solution for their loved ones across home care, independent living, memory care, assisted living, and more.. A Place for Mom is looking for a Staff Machine Learning Engineer to help build practical, data-driven machine learning applications focused in the Engineering space.. This position reports to the VP of Engineering and works directly in the Engineering organization while also working closely with the Data Science team which includes data scientists and machine learning engineers.. Deep understanding of real-time inference systems, streaming data pipelines, model serving services, feature store monitoring and latency optimization for ML & LLM applicationsSolve complex problems with multilayered data sets and optimize existing machine learning libraries and frameworks.. Technical Skills: Expertise in SQL, Databricks, AWS services, Python, Spark and machine learning frameworks such as XGBoost, Scikit, TensorFlow, Keras or PyTorch.
This may involve data exploration, high-performance data processing, and machine learning algorithm exploration.. This may involve speeding up training, making a data processing easier, or data management tooling.. Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).. Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).. Discover data sources, get access to them, import them, clean them up, and make them “machine learning ready”.
You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: computer vision, graph neural network, natural language processing (NLP), inclusive AI, reinforcement learning, user modeling, and recommender systems.. Contribute to cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems. Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across growth, discovery, ads and search. MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field. Python) or one ML framework (Tensorflow, Pytorch, MLFlow)