Machine Learning Engineer Salary in Pittsburgh, Pennsylvania

At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of AI technologies and systems. We currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security. As our government customers adopt AI and machine learning to provide leap-ahead mission capabilities, we •build real-world, mission-scale AI capabilities through solving practical engineering problems •discover and define the processes, practices, and tools to support operationalizing AI for robust, secure, scalable, and human-centered mission capabilities •prepare our customers to be ready for the unique challenges of adopting, deploying, using, and maintaining AI capabilities •identify and investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape Are you creative, curious, energetic, collaborative, technology-focused, and hard

Position Overview At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company's success. As a Senior Machine Learning Model Developer within PNC's Fraud Modeling organization, you will be based in Pittsburgh, PA, Columbus OH, New York, Dallas, TX, Washington DC, Charlotte, NC, or Wilmington, DE. The position is primarily based in a PNC location. Responsibilities require time in the office or in the field on a regular basis. Some responsibilities may be performed remotely, at the manager's discretion. PNC will not provide sponsorship for this position. Preferred Skills: Python, Pyspark Job Description Leads the implementation of analytical projects that leverage vast amounts of structured and unstructured dat

Job Title: ML OPS Engineer Job Location: Hybrid (Pittsburgh, PA / Cleveland OH) Job Type: Full Time Qualifications Bachelor’s degree in Computer Science or Software Engineering Having 7 years in Software Engineering Hands-on experience working with at least one cloud (AWS) Ability to build MLOps pipelines on AWS Sage Maker. Hands-on DevOps experience – CI/CD in Jenkins, Bitbucket, Kubernetes, and OpenShift. Good to have in-depth knowledge of machine learning frameworks or libraries such as TensorFlow, Keras, PyTorch, etc Ability to understand tools used by data scientists and experience with software development and test automation Experience with Agile development and delivery – Scrum, Lean, XP, Kanban methodologies. Proficiency in modern programming languages such as Python. AWS Machine Learning certification is a huge plus

Summary of the role: In this role you will help to develop, build, design, continuously improve, and support the MLOps Platform at PNC. You will participate in all stages of development, use various software and tools, and enabling self-service tools for data science teams. The role also involves designing, developing, integrating, and deploying tools for Data Science and Machine Learning (ML) Research. The successful applicant will design and operate a framework for Machine Learning Operations (MLOps), advise on software engineering for ML, and ensure consistency with cloud architectural principles. About the role: Be able to design, implement, and operate a framework for Machine Learning Operations (MLOps) on cloud (AWS) Build MLOps pipelines orchestration on Amazon SageMaker Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality Design, develop, integrate, and deploy tools for Data Science and ML

Summary of the role: In this role you will help to develop, build, design, continuously improve, and support the MLOps Platform at PNC. You will participate in all stages of development, use various software and tools, and enabling self-service tools for data science teams. The role also involves designing, developing, integrating, and deploying tools for Data Science and Machine Learning (ML) Research. The successful applicant will design and operate a framework for Machine Learning Operations (MLOps), advise on software engineering for ML, and ensure consistency with cloud architectural principles. About the role: Be able to design, implement, and operate a framework for Machine Learning Operations (MLOps) on cloud (AWS) Build MLOps pipelines orchestration on Amazon SageMaker Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality Design, develop, integrate, and deploy tools for Data Science and ML

PPG Industries, Inc., headquartered in Pittsburgh, PA, has a work-at-home Data Engineer Analyst position (w/ability to telecommute w/approp. telecommuting sys.; remote worksite must be w/in commuting distance of Pittsburgh, PA for weekly trips to corp. office) responsible for developing & building AI/ML model-ready data ponds. Apply online at careers.ppg.com. - - - - - - - - - - - - - - - - - - - - - -- - - - - - - - - - -- - - - - - - - - - -- - - - - - - - - - -- - - - - - - - - - -- - - - - - - - - - -- - - - - - - - - - -- - - - - - - - - - -- - - - - - - - - - -- - - - - - - - - - -- - - - - - - - - - -- - - - - - - - - - - recblid mokdix2p50j7q03hag94yscmsdetaj