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Experience with red team operations or offensive cyber capabilities development. Familiarity with the AI/ML software stack (e.g. CUDA, PyTorch, TensorFlow, Ray). A PhD in Computer Science, Computer Engineering, Electrical Engineering, Cybersecurity, Information Security, Information Technology, Mathematics, Applied Mathematics, Physics, Applied Physics, Engineering Physics, Artificial Intelligence, Machine Learning, Engineering and Public Policy, Technology and Policy, National Security Policy, Policy Analysis, Political Science, International Relations, or similar with at least 3 years of relevant professional experience is required.. We are hiring for this position in San Francisco, CA;Washington, DC; Santa Monica, CA; Pittsburgh, PA; and Boston, MA. We offer a hybrid work arrangement, combining work from home and on-site options.. Fully remote work will also be considered.
REPORTS TO: Program Director and/or as assigned. Play & Learn Staff play an integral role in the development of building strong character values in youth.. There will be a direct focus on member retention, member recruitment, safety, and customer service.. All staff must strive to work cooperatively with fellow employees to achieve the goals and objectives of the YMCA. Promote member incentive programs each branch offers, such as Parents' Night Out.
Seeking a Machine Learning Engineer to maintain, enhance, and productionize an existing predictive model that estimates the average duration of construction jobs.. You’ll work with historical workflow data, improve model accuracy, and explore new ML opportunities once the current model is stable.. Python – strong proficiency for data manipulation & model implementation.. Applied Machine Learning – hands-on experience with regression, classification, or similar predictive modeling techniques.. Work with historical workflow data to refine accuracy and reliability.
🚀 Publish, present, and patent high-impact findings in AI and machine learning.. Conduct cutting-edge research in artificial intelligence, including areas such as natural language processing, computer vision, generative models, and reinforcement learning.. Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ACL, CVPR, ICLR) is highly preferred.. Expertise in machine learning, deep learning, or statistical modeling.. Experience with model development using TensorFlow, PyTorch, JAX, or similar frameworks
Design and maintain fraud rules and scoring logic for transaction monitoring systems. Ensure alignment with regulatory expectations, model risk governance, and internal audit requirements. Explore and implement new technologies (e.g., graph analytics, behavioral biometrics, NLP) for advanced fraud detection. Strong command of Python, R, SQL, and data science libraries (pandas, scikit-learn, TensorFlow, etc.. Exposure to real-time fraud systems (e.g., SAS Fraud Management, Actimize, Falcon, etc.)
Fully Remote (onsite in Vinings, GA from Mon-Thurs if converted to FTE). We are seeking a Senior BI Analyst with expertise in Python, SQL, Tableau, and predictive analytics.. You will work with large datasets across SAP and Snowflake environments to deliver strategic insights, with a strong focus on forecasting container arrivals, optimizing inventory levels, and identifying cost-saving opportunities – all in support of a major ERP modernization and the nationwide consolidation of distribution centers.. System Migration : Lead data analysis and reporting for a major migration from a legacy ERP to SAP Warehouse Management, with reporting transitioning to Snowflake.. Python Predictive Analytics : Perform predictive modeling in Python to forecast container arrivals, inventory levels, and other supply chain KPIs.
Broad technical foundation in software engineering and deep learning (through self-study, practical experience, or PhD).. ML: knows the theory and applied side of deep learning, especially computer vision and foundational model architectures (PyTorch, OpenCV, Tensorflow).. Backend: experience designing and building scalable and high availability server-side systems (Python, NodeJS, or Golang).. Cloud: familiarity with DevOps and infrastructure (i.e. Docker, Kubernetes, GPU scheduling) on cloud (i.e. GCP, AWS).. Monitoring: experience with logging systems and monitoring tools such as DataDog, Sentry, and/or CloudWatch
A company at the intersection of AI and Life Sciences is looking to expand their highly successful AI Research team.. The company is based in the San Francisco Bay Area, but the role may be open to fully remote.. Libriaries: PyTorch, Tensorflow, Scikit-learn, Pandas. Neural Networks: Graph Neural Networks, CNN. Protein Language Models: AlphaFold, etc.
You’ll lead high-impact client engagements focused on Generative AI, Agentic AI, MLOps, and AI governance frameworks — driving measurable outcomes in upstream, midstream, and downstream operations.. Define and implement enterprise-wide AI and quantitative modeling strategy tailored to oil & gas value chains (e.g., asset optimization, drilling, trading, predictive maintenance).. Establish AI governance frameworks that ensure responsible AI adoption, ethical use of data, model risk management, and alignment with evolving regulations.. Prior experience leading AI initiatives in the energy or oil & gas sector, including exploration, refining, or energy trading.. AI certifications (Microsoft, AWS, NVIDIA, Databricks, or equivalent).