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As a dedicated Director, Data Scientist, you will lead a team of Data Scientists responsible for identifying, scoping, and translating business problems into applied statistical, machine learning, simulation, and optimization solutions to inform actionable business insights and drive business value through automation, revenue generation, and expense and risk reduction.. Responsible for the team’s model inventory and ensures compliance with USAA model risk policies and regulatory expectations.. 8 years in predictive modeling, model governance, machine learning and large data analysis., OR Advanced Degree (e.g., Master’s, PhD) in Mathematics, Statistics, Data Science, Computer Science, or related quantitative STEM field (Science, Technology, Engineering and Math) field and 6 years in predictive modeling, model governance, machine learning and large data analysis.. Experience with various languages, applications, and technologies (such as SQL, Python, R, Spark, Hadoop etc.). Experience in developing and reviewing modeling solutions based on broad range of techniques – e.g., linear and logistic regressions, time series methods, survival analysis, support vector machines, neural networks, decision trees, random forests, gradient-boosting methods, deep learning, k-means and other clustering methods, simulation methods, or other advanced techniques.
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)
Leidos is looking for a Enterprise Architect to support a large program within a Federal Law Enforcement Agency.. 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).
As a dedicated Director, Data Scientist, you will lead a team of Data Scientists responsible for identifying, scoping, and translating business problems into applied statistical, machine learning, simulation, and optimization solutions to inform actionable business insights and drive business value through automation, revenue generation, and expense and risk reduction. Responsible for ensuring all modeling and machine learning solutions adhere to industry standards, model risk policy, and regulatory expectations. 8 years in predictive modeling, model governance, machine learning and large data analysis., OR Advanced Degree (e.g., Master's, PhD) in Mathematics, Statistics, Data Science, Computer Science, or related quantitative STEM field (Science, Technology, Engineering and Math) field and 6 years in predictive modeling, model governance, machine learning and large data analysis. Experience with various languages, applications, and technologies (such as SQL, Python, R, Spark, Hadoop etc. Experience in developing and reviewing modeling solutions based on broad range of techniques – e.g., linear and logistic regressions, time series methods, survival analysis, support vector machines, neural networks, decision trees, random forests, gradient-boosting methods, deep learning, k-means and other clustering methods, simulation methods, or other advanced techniques.
The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory.. We’re looking for a senior Machine Learning Data Scientist to lead our forecasting initiatives.. You’ll be one of the founding members of the Forecasting pillar within Strategic Finance Data Science, responsible for building and scaling robust, interpretable, and production-ready forecasting systems.. 7+ years of experience in applied data science, with deep hands-on exposure to forecasting, predictive modeling, or marketplace systems.. SQL , and tools such as scikit-learn, PyTorch/TensorFlow, and forecasting libraries.
Crowdstrike’s Data Science team is expanding – we are looking for a Senior Machine Learning Engineer to join our growing Data Science organization.. Automate and visualize analyses, results and processes in our artificial intelligence and machine learning pipeline. Python (xgboost, pytorch, tensorflow, scikit-learn, pandas, huggingface). Proven track record working with distributed compute systems (e.g. Spark, Ray, etc) running on a cloud provider such as AWS or GCP. The base salary range for this position in the U.S. is $135.000 - $215.000 per year + variable/incentive compensation + equity + benefits.
We are seeking a highly motivated, self-starter Machine Learning Engineer to join our AI/ML Engineering team to help achieve this mission.. Expert in multiple Programming/scripting languages, i.e. Unix/Linux Shell Scripting, Python, Java, Scala.. Expertise in Big Data technologies such as Hadoop, Spark, HBase, Kafka.. Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).. Good understanding of machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, etc.
We’re seeking a Senior Machine Learning Engineer to join our Data Services and Moderation team within Unity Ads!. You’ll collaborate with teams of data scientists, software developers, and product managers to design, develop, and deploy various deep learning and LLM/RAG solutions, and ensure their integration into our Unity Ads infrastructure. Proficient and strong knowledge in Python, Terraform, cloud platforms (GCP/AWS), Docker, K8, Kafka, Github Actions, serverless, and SQL. Familiar with Numpy, Tensorflow, Pytorch, vector DB, neural networks, computer vision, LLM, RAG and general ML concepts. Proficiency in data manipulation and analysis using tools like SQL, BigQuery, Pandas, and/or Spark, along with experience in data visualization and dashboarding.
As a Data Scientist / Data Analyst / Data Science Specialist for Adidev Technologies Inc., you will be enhancing and debugging large-scale applications for one of our well-known clients. Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation-systems, environmental systems and/or agronomic problems. Practical knowledge and experience with cloud-computing systems and platforms, including the routine deployment of pipelines through Kubernetes.. Apply Natural Language Processing and Computer Vision to solve business use cases,.. Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipelines construction
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. Hands-on experience with cloud platforms (Azure, AWS, or Google Cloud) for building scalable data solutions. 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).
As the Senior Staff Data Scientist, you will be at the forefront of developing and delivering innovative algorithms that generate actionable business insights for key areas within GE HealthCare, including Finance, Commercial, Supply Chain, Quality, Operational Excellence and Lean, and Manufacturing. PhD in Computer Science, Data Science, Engineering or a STEM related field with a focus on neural networks and computer vision. Proficiency in the latest Python, AWS, Azure, and open-source data science tools such as Jupyter, R, SQL, Hadoop, Spark, TensorFlow, Keras, PyTorch, and Scikit-learn. Experience with image processing techniques and libraries like OpenCV. Ability to continuously track, evaluate, adapt the latest advancements in deep learning techniques and AI/ML research to business use cases across GE HealthCare.
As a dedicated Director, Data Scientist, you will lead a team of Data Scientists responsible for identifying, scoping, and translating business problems into applied statistical, machine learning, simulation, and optimization solutions to inform actionable business insights and drive business value through automation, revenue generation, and expense and risk reduction.. Responsible for ensuring all modeling and machine learning solutions adhere to industry standards, model risk policy, and regulatory expectations.. 8 years in predictive modeling, model governance, machine learning and large data analysis., OR Advanced Degree (e.g., Master’s, PhD) in Mathematics, Statistics, Data Science, Computer Science, or related quantitative STEM field (Science, Technology, Engineering and Math) field and 6 years in predictive modeling, model governance, machine learning and large data analysis.. Experience with various languages, applications, and technologies (such as SQL, Python, R, Spark, Hadoop etc.). Experience in developing and reviewing modeling solutions based on broad range of techniques – e.g., linear and logistic regressions, time series methods, survival analysis, support vector machines, neural networks, decision trees, random forests, gradient-boosting methods, deep learning, k-means and other clustering methods, simulation methods, or other advanced techniques.
Has obtained a Ph. D. degree in Machine Learning, Artificial Intelligence, Computer Science, Information or Multimedia Retrieval, Reinforcement Learning, Mathematics, or relevant technical field.. Experience with deep learning frameworks such as Pytorch or Tensorflow.. Experience building systems based on machine learning, reinforcement learning and/or deep learning methods.. Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICLR, AAAI, RecSys, KDD, IJCAI, CVPR, ECCV, ACL, NAACL, EACL, ICASSP, or similar.. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
We are an interdisciplinary team with backgrounds in Computer Science, ML/AI, Electrical Engineering, Computer Engineering, Physics, Neuroscience, Economics, and VLSI Design, united by our passion to solve challenging problems. About the Role: We are seeking a highly skilled Applied ML Research Engineer to research, develop, and deploy solutions to accelerate the chip design process and who is passionate about building, delivering, and seeing their work realized in end-to-end products used to design Qualcomm chips. Strong background in machine learning, deep learning, and statistical modeling. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). Experience with big data technologies such as Hadoop, Spark, and cloud platforms like AWS, Azure, or Google Cloud.
Director, Artificial Intelligence and Machine Learning (AI/ML) Quality Oversight United States - Maryland - Frederick, United States - California - Santa Monica, United States - California - Oceanside Quality Regular.. Ensure the quality and reliability of Natural Language Processing (NLP) solutions developed for tasks including sentiment analysis and automation. Define quality standards and oversee the development and implementation of deep learning models for complex applications such as image and speech recognition and autonomous systems. PhD in degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field with 8+ years of progressive experience in developing and deploying machine learning models and AI solutions, with a strong emphasis on quality assurance and oversight OR. Hands-on experience with NLP, deep learning frameworks (e.g., TensorFlow, PyTorch), and deploying models in production environments, with a quality-centric approach.
We are seeking mid-level Artificial Intelligence engineers who will help develop AI technologies that adapt and scale to solve sophisticated problems across a variety of problem domains. A general understanding of machine learning algorithms including deep learning, neural network design, deep reinforcement learning, large language models (LLMs), and computer vision. Common machine learning frameworks such as PyTorch, TensorFlow, or Jax. LLM frameworks such as HuggingFace, including retrieval-augmented (LangChain, Llama-Index) optimizing / agentic LLM stacks (DSPy, Smolagents, etc), and parameter-efficient fine-tuning (LoRA, Q-LoRA). LLM inference servers (TGI, vLLM, etc).
When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. A master's or Ph. D. degree in computer science, machine learning, artificial intelligence, or a related field. Experience with cloud platforms (e.g., AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark, Hadoop). Expertise in generative AI, ML algorithms, and frameworks such as Hugging Face, Tensorflow, PyTorch, etc. Strong understanding of deep learning architectures, natural language processing, computer vision, and other relevant areas of machine learning.
As a Solutions Architects on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.. Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows.. 5+ 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)
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.. Experienced in developing, deploying, and serving scalable LLM applications in production environments.
Work or educational background at minimum of a Master's degree in one or more of the following areas: machine learning, computational linguistics, Fraud Analysis, Time series Analysis, deep learning, ratification intelligence, data science and/or data analytic, generative AI, symbolic AI, causal AI, operations research, computer science, Mathematics, business analytics, or knowledge management.. Proficient with Amazon AWS Sagemaker, Jupyter Notebook and Python Scikit, Deep Learning, Machine Learning tools such as TensorFlow. Experience with image processing models such as Coco, CLIP, ResNet or comparable models. Proficient in FRAUD DETECTION and Time Series Analysis plus Natural language processing (NLP) and Natural language generation (NLG) including prior projects in any of the following categories: top modeling of text, sentiment analysis of text, part of speech tagging, Name Entity Recognition (NER), Bag of Words, text extraction. Demonstrated experience with SQL and any relational database technologies, such as Oracle, PostgreSQL, MySQL, RDS, Redshift, Hadoop EMR, Hive, etc.