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Lead end-to-end AI/ML development for payments, building generative and agentic systems on cloud infrastructure while ensuring scalable, secure, and compliant production deployment.
Builds and maintains data pipelines using SSIS/Fabric to extract, transform, and load data for business reporting; ensures data quality and collaborates with analysts to deliver dashboards and insights.
Senior ML Engineer building fraud detection and identity security models (credential stuffing, ATO) at Disney, using Python, scikit-learn, pandas, and TensorFlow/PyTorch on large-scale data.
The Senior Machine Learning Engineer will design, develop, and deploy machine learning and generative AI models into production environments. The role involves building scalable pipelines, fine-tuning LLMs, and collaborating with cross-functional teams to integrate AI solutions using technologies like Python, PyTorch, and Azure.
Data Scientists at Westpac will develop and deploy machine learning models, including predictive, NLP, and GenAI solutions, within a hybrid cloud environment. The role involves owning the full lifecycle of data science use cases, from problem framing to production, while collaborating with engineering teams to deliver explainable and maintainable solutions.
The Software Engineer will support Army aviation data initiatives by applying AI/ML principles to big data storage, manipulation, and analysis. The role involves modeling and predicting outcomes using machine learning frameworks and statistical analysis tools.
The Senior Data Scientist will develop predictive models and perform advanced statistical analysis on healthcare datasets to improve patient outcomes and clinical workflows. The role requires expertise in Python, SQL, and big data frameworks to build AI-powered healthcare applications.
Design, develop, deploy, and maintain AI/ML models on AWS GovCloud using SageMaker, Databricks, PySpark, and Delta Lake for federal government programs, ensuring compliance with NIST AI RMF, EO 14110, and FedRAMP standards.
AI Software Developer Intern at Booz Allen supporting Navy cybersecurity and mission projects in San Diego, writing Python code and applying AI/ML tools in a secure government consulting environment.
Develop and deploy machine learning and generative AI applications—including LLMs, RAG pipelines, and GenAI services—using Python, PyTorch, Azure, and vector databases in an on-site role at HP.
Join us as a Lead AI Engineer and play a key role in shaping the future of AI across Customer Operations. We're looking for a technical leader who enjoys solving complex challenges, building innovative AI products…
We're looking for a hands-on AI Engineer who is passionate about turning emerging AI technologies into practical solutions that deliver real business value. Working within our Customer Operations team, you'll…
COMPANY OVERVIEW We exist to make food the world loves. But we do more than that. Our company is a place that prioritizes being a force for good, a place to expand learning, explore new perspectives and reimagine new…
Mid-level Data Scientist building machine learning and applied AI solutions for clients using Python, Databricks, and cloud platforms (GCP, Azure) in a remote, Americas-collaborative role.
Mid-to-senior Data Scientist covering the full ML/AI lifecycle—traditional ML, LLMs, RAG, and agentic AI workflows—deployed on AWS with MLOps practices, for a US insurance-focused company's Belfast hub.
Build predictive models, time-series forecasts, and generative-AI tools to automate sales insights and optimize revenue for AMD’s Sales Operations team using Python, SQL, and ML frameworks.
Evaluate AI-generated data science solutions and ML outputs for accuracy and reasoning quality on a part-time hourly contract, using Python, SQL, and statistical modeling expertise.
Evaluate AI-generated data science solutions, statistical analyses, and machine learning outputs for accuracy and technical soundness, providing structured expert feedback to improve next-generation AI systems using Python, SQL, and ML frameworks.
Designs and leads enterprise-scale AI/ML and Generative AI solutions, focusing on LLMs, RAG architectures, and cloud-based deployments while mentoring teams and ensuring governance.
Leads ML/AI operations for GoFundMe’s production systems, ensuring reliability, scalability, and safety of ML pipelines, model serving, and observability infrastructure. Manages a team to optimize ML lifecycle from data to deployment, balancing innovation with operational rigor.
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