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The Data Science team at Meijer leads the strategy, development and integration of Machine Learning and Artificial Intelligence at Meijer.. 8+ years of relevant data science experience in an applied role – preferable w/in retail, logistics, supply chain or CPG with a focus on NLP and AI. Advanced and hands on experience using: Python, Databricks, Azure ML, Azure Cognitive Service, Ads Data Hub, BIQuery, SAS, R, SQL, PySpark, Numpy, Pandas, Scikit Learn, TensorFlow, PyTorch, AutoTS, Prophet, NLTK. Experience with Azure Cloud technologies including Azure DevOps, Azure Synapse, MLOps, GitHub. Solid experience working with large datasets and developing ML/AI systems such as: natural language processing, speech/text/image recognition, supervised and unsupervised learning models, forecasting and/or econometric time series models
A story about innovations and traditionsabout inspiring stores and irresistible productsabout the excitement of the Macys 4th of July Fireworks, and the wonder of the Thanksgiving Day Parade. The Senior Data Scientist designs, develops, and implements advanced data science models for priority business use cases across the enterprise. 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.
You will apply cutting-edge techniques from deep learning, language modeling, recommender systems, and more to integrate artificial intelligence into our product and bring customers value.. You should have broad and in-depth experience in machine learning or data science, especially in the domain of deep learning, recommender systems, NLP, generative AI, or related areas.. Experience with machine learning frameworks such as Huggingface, PyTorch, Tensorflow, Keras; Experience with distributed training with Spark, Ray, etc.. Deep understanding of the latest AI technologies and their application in business contexts, including deep learning, recommendation systems, NLP, generative AI, or related areas.. In addition to base salary, our total compensation package may include participation in the company’s annual cash bonus plan, variable compensation (OTE) for sales and customer success roles, equity, sign-on payments, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility.
Requires at least 3 years of professional Data Science or ML experience, or a Ph. D. in operations research, applied statistics, data mining, machine learning, or a related field.. Proficiency in open-source languages such as Python, R, and Julia.. Experience with cloud platforms like Azure and Google Cloud; experience with DataBricks is a plus.. Understanding of statistical methods and advanced modeling techniques (e.g., SVM, K-Means, Random Forest, Boosting, Bayesian inference, NLP).. Experience with machine learning and deep learning frameworks (scikit-learn, XGBoost, TensorFlow, PyTorch).
- Designing and developing machine learning and deep learning systems.. - Running machine learning tests and experiments.. - Inventing and deploying innovative technologies. PhD in Machine Learning, Neural Networks, Data Science, Computer Science, applied math, or related quantitative field -OR-. 10+ years of work experience leading and managing teams/projects related to Machine Learning, Neural Networks, and Artificial Intelligence.
I developer / Machine Learning Engineer Fulltime Local to Bay Area Preferred s an ML Engineer, you will play a crucial role in the development and implementation of cutting-edge artificial intelligence products and services. To be successful, you must possess exceptional skills in programming, as well as an understanding of data science and software engineering using ML frameworks for Natural Language Processing (NLP). Keep abreast of the latest AI models (LLMs and others) and techniques in NLP. Fine-tune, prompt-train, train and retrain open-source AI models on customer data. Identify the best available open-source AI models, libraries, and approaches to NLP. Run machine learning tests and experiments to update and improve ITSoli's accelerators. Requirements and skills Proven experience as a Machine Learning Engineer or similar role with NLP. bility to write robust code in Python, Java, and R Familiarity with machine learning frameworks (like Keras or PyTorch), libraries (like scikit-learn) and LLMs. Excellent communication skills.
Summary: TRABUS seeks a highly motivated Machine Learning Engineer to join our dynamic team.. In this role, you will leverage your expertise in machine learning algorithms and software engineering to contribute to diverse AI projects related to resource planning for ship maintenance, marine transportation, and climate/environmental informatics.. Collaborate with the Data Science team to deliver scalable AI solutions involving LLMs, RAG, prompt engineering, computer vision, and NLP tools.. Completed coursework in Machine Learning, Deep Learning, Algorithms, and Data Science.. Excellent Python coding skills, experience with large datasets, and familiarity with web frameworks like Django and Flask.
Description :At Regions, the Risk Data Scientist researches, models, implements, and validates algorithms (predictive and prescriptive) to analyze diverse sources of data to achieve targeted outcomes.. The position at this level works with multiple teams of data scientists, analysts, and visualization experts contributing independently to solve business problems with high complexity and enable effective risk management.. Additionally, the position at this level requires in-depth knowledge in quantitative analytical methods, data management, visualization, and programming skills suitable to drive data-driven decisions.. Primary ResponsibilitiesWorks with large, structured, and un-structured datasetsUses quantitative and analytical techniques to accelerate profitable growth and monitor and mitigate risk - unlocking value across all functional areas of businessUses Big Data tools (e.g. Hadoop, Spark, H2O, CDSW, Domino Labs, etc.). The target information listed below is based on the Metropolitan Statistical Area Market Range for where the position is located and level of the position.
Principal Engineer, AI & Machine Learning This role is eligible for our hybrid work model: Three days in-office.. Python, Tensorflow, Keras, Spark, Numpy, Pandas, Spacy and many other tools and libraries, Vertex. We train our models using GCP Vertex and deploy services in Kubernetes and using GCP.. Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and big data technologies (e.g., Spark).
As a Machine Learning Scientist - Natural Language Processing (NLP) - Senior Associate in the Chief Data & Analytics Office (CDAO) at JPMorgan Chase, you will have the unique opportunity to apply sophisticated machine learning methods to complex tasks.. Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as NLP, speech recognition and analytics, time-series predictions or recommendation systems. Solid background in NLP or speech recognition and analytics, personalization/recommendation and hands-on experience and solid understanding of machine learning and deep learning methods. Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas). Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
This role requires a strong foundation in AI-driven data analysis, data engineering, and visualization, as well as the ability to communicate complex findings to non-technical audiences.. Strong programming skills in Python, R, or SQL for data analysis and model development.. Hands-on experience with AI/ML frameworks such as TensorFlow, Scikit-learn, PyTorch, or similar.. Strong statistical foundation for hypothesis testing, A/B testing, and predictive modeling.. Proficiency with Tableau, Power BI, Seaborn, Matplotlib, or other visualization tools.
Responsibilities The AI Platform, Principal Engineer is responsible for designing, building, and maintaining robust AI platforms that support advanced machine learning and artificial intelligence applications.. Experience with cloud platforms (AWS, Azure) and containerization technologies (Docker, Kubernetes).. Excellent knowledge of MySQL, SQL Server, PostgreSQL, MongoDB, and/or CosmosDB. Multiple years working with structured and unstructured data within a cloud-based data environment (Redshift, Data Bricks, Hadoop, Snowflake, Spark, unmanaged Kafka, etc. Experience with Master Data Management (MDM) systems and processes.
Lead, mentor, and scale a high-performing team across data engineering, data architecture, data governance, and Artificial Intelligence/Machine Learning (AI/ML). Lead data engineering teams to ensure reliable, high-quality data delivery and real-time streaming capabilities. Good understanding of Python, R, SQL, RDBMS, NoSQL databases and big data solutions, architecture issues. Experience with AI frameworks (TensorFlow, PyTorch), orchestration tools (Airflow, Kubeflow), and data visualization platforms (Tableau, Power BI). Driscoll's exclusive patented berry varieties are developed through years of research using only natural breeding methods – meaning, no GMOs. From farm-to-table, we focus on delivering a high quality, premium berry experience with our many supply chain partners.
We are seeking a highly skilled and motivated Machine Learning Engineer to join our team.. Work with data engineers to ensure data quality and integrity for machine learning projects. Experience with programming languages such as Python, R, and Java. Familiarity with machine learning libraries and frameworks such as TensorFlow, Keras, and PyTorch. If you are a driven and innovative Machine Learning Engineer looking to make a difference in the construction industry, then we want to hear from you!
We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society.. Position Overview 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.. Preferred Qualifications 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.
We are looking to assemble a skilled development team to build an Expert Advisor (EA) designed to deliver a consistent high return on investment (ROI) by leveraging advanced technologies such as machine learning, deep learning, and other algorithmic trading tools.. Integrate machine learning techniques (e.g., neural networks, reinforcement learning, genetic algorithms) to analyze market data and generate adaptive trading signals.. Ensure the EA includes comprehensive risk management modules, such as dynamic stop-loss and take-profit adjustments.. Algorithmic Trading Expertise: Proven experience in developing and deploying Expert Advisors or automated trading systems.. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and statistical analysis.
Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded.. During your internship, you will have the opportunity to collaborate with AMD leaders, receive one-on-one mentorship, attend amazing networking events, and much more.. If you have knowledge or experience with any of the following technical skills (or related areas) and are enthusiastic about this role, we strongly encourage you to apply – Machine learning, data science, computer vision, statistics, and mathematics Programming in Python, C/C. Relational (SQL) and no-SQL databases Machine learning algorithms and frameworks Deep learning / AI framework like Pytorch, Tensorflow, Caffe.. Familiarity with cloud (e.g., AWS, GCP, Azure) Note: By submitting your application, you are indicating your interest in AMD intern positions.
The role is focused on recommender systems bridging Generative AI, Natural Processing (NLP), Reinforcement Learning (RL), graph networks, and deep learning to help find the next great read for Books customers.. You will build recommendation model pipelines, identify technical opportunities within complex deep learning-based recommendation models, and work with engineering and product leaders to power customer-facing recommendations.. Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.. PREFERRED QUALIFICATIONS- Experience with popular deep learning frameworks such as MxNet and Tensor Flow. Experience with large scale distributed systems such as Hadoop, Spark etc.
Develop, validate, and deploy predictive models using machine learning techniques to address telecom challenges, such as customer churn prediction, fraud detection, and network demand forecasting.. Proficiency with machine learning libraries and tools such as Scikit-Learn, TensorFlow, PyTorch, and XGBoost.. Familiarity with big data tools like Apache Spark, Hadoop, or Hive for large-scale data processing.. Experience with deep learning, natural language processing (NLP), or anomaly detection for telecom applications like sentiment analysis or network monitoring.. Relevant certifications like AWS Certified Machine Learning, Google Professional Machine Learning Engineer, or telecom-related certifications.
As a Data Scientist, you will play a crucial role in driving data analysis, insights, and predictive modeling to support our business operations and deliver valuable solutions to our clients.. Assist in the development and implementation of data governance policies, data quality standards, and best practices.. Experience with statistical analysis, data mining, and predictive modeling techniques.. Proficient in machine learning algorithms and libraries / frameworks, such as scikit-learn, TensorFlow, or PyTorch.. Skilled in data visualization and storytelling using tools like Tableau or Power BI.