Machine Learning Jobs in Richardson, TX

Deploy, maintain, and improve production ML workflows and platforms for media measurement and customer analytics on AWS. Build SageMaker jobs and endpoints, orchestrate pipelines with Step Functions, Lambda, and Airflow, manage model artifacts and CI/CD, troubleshoot production issues, and collaborate on platform enhancements and operational best practices.

Early-career role to characterize AI/ML workloads, build performance and hardware-mapping models, identify compute/memory/power bottlenecks, collaborate with SoC/IP and compiler teams, and communicate results via reports and design reviews.

Design and deploy scalable machine learning models, analyze data, and improve model performance in a collaborative environment.

Lead high-impact AI/ML projects in the automotive domain, overseeing technical strategy, project execution, and client management, while mentoring junior team members.

The ML Engineer will develop and deploy machine learning models, collaborate with teams, analyze datasets, and improve model performance.

Build, deploy, and monitor ML/AI models end-to-end: research and implement algorithms, design ML approaches, analyze and visualize data, ensure model performance in production, collaborate with stakeholders and cross-functional teams, and mentor junior engineers.

Design and implement high-performance APIs and microservices using Python and AWS, focusing on generative AI and scalable applications.

Lead RTL development and microarchitecture for an AI-enabled RISC-V CPU core, including vector and matrix engines. Define features, optimize performance/power/area, support verification and simulation, collaborate with CPU modeling and physical design teams, and ensure design meets timing, reliability, testability, and power goals.

Lead workload-driven AI/ML architecture across hardware and software: characterize workloads, perform system-level performance and memory analysis, define measurement and pre-silicon estimation methods, leverage MLIR/IREE toolchains, identify bottlenecks, recommend SoC/CPU/memory optimizations, and present findings to engineering leadership while mentoring junior engineers.

Lead RTL development and microarchitecture of an AI-enabled RISC-V CPU core, including vector and matrix engines. Drive design for performance, power, area, verification support, and SoC integration while collaborating with cross-functional teams to meet timing, reliability, testability, and power goals.

Lead design and implementation of agentic AI/ML solutions and modern software (APIs, microservices, CI/CD, streaming) on cloud platforms. Bridge legacy IBMi AS400 systems with modern AI, train and fine-tune models, oversee lifecycle, mentor engineers, set technical direction, and improve automation and testing across claims adjudication systems.

The Senior Machine Learning Engineer will design and deploy ML models, analyze large datasets using PySpark, and collaborate across teams in a cloud environment.