Top Senior Machine Learning Jobs in Atlanta, GA

The Engineering Manager will lead teams in developing and managing Blackbaud's Data & AI platform, focusing on scalability, security, and cost-efficiency.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.

The Partner Enablement Technical Lead will design and manage technical learning programs for partners, focusing on Data & AI technologies, and align strategies with business needs to enhance partner proficiency.

Manage technical programs for generative AI video models, translating research into milestones, coordinating teams, and ensuring successful execution across all phases.

Lead the development and integration of advanced AI solutions, focusing on scalable AI models and collaborating with cross-functional teams.

As a Senior Machine Learning Engineer, you will design and deploy ML models to optimize clinical trial workflows, mentor junior engineers, and collaborate with cross-functional teams to enhance patient engagement.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

As a Staff Machine Learning Engineer, you will develop, productionize, and deploy ML models for clinical use, ensuring real-world effectiveness through hands-on coding and infrastructure building.

The role involves improving machine learning ranking models, implementing algorithms, and taking full ownership of machine learning systems within Quora's product.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

As a Senior MLOps Engineer, you will manage production ML systems, define lifecycle strategies, optimize ML pipelines, and collaborate with cross-functional teams to enhance ML operations.

Design and build machine learning models for Zillow's product features, optimize AI components, and mentor engineers within a cross-functional team.

As a Senior Machine Learning Engineer, you will design and train ML models for logistics, manage their production deployment, and optimize their performance while collaborating with the data science team.

The Senior ML Engineer will design evaluations for AI features, optimize pipelines, and ensure quality in ML systems while collaborating with cross-functional teams.

The role involves defining and building the company's machine learning capabilities, designing production ML systems, owning data strategy, and partnering with engineers. Requires experience in ML system production and software engineering fundamentals.

The role involves defining and building ML capabilities, creating production systems, and managing data strategy while collaborating with engineers and leading an ML team.

The Machine Learning Engineer will design and build systems that improve the AI shopping agent by using real user feedback, focusing on feedback loops and metrics to enhance user interactions and agent performance.

Design, build, and deploy scalable ML models and data pipelines for prediction, anomaly detection, personalization, and automation. Own operationalization, monitoring, model evaluation, and integration with platform services at cloud scale.

The Sr. Machine Learning Engineer will build tooling and services for ML and generative AI solutions, focusing on deployment, evaluation metrics, and cross-functional collaboration.

As an ML Platform Engineer, you will enhance the core ML platform's performance and scalability, enabling faster innovation and impactful machine learning solutions.

Lead design, development, and productionization of advanced ML models and data pipelines. Drive architecture, experimentation, validation, and best practices while mentoring ML engineers and delivering scalable, business-driving AI solutions.

The role involves building bioinformatics and ML pipelines, analyzing multi-omics data, mentoring, and collaborating across teams to develop actionable insights and scientific breakthroughs.

Lead a team of data scientists developing ML-driven products, managing infrastructure, training models, and ensuring production quality while collaborating with senior leadership.

Lead and grow a global data engineering and ML organization, design cloud-native data platforms and pipelines, deliver ML-powered products, establish engineering and MLOps best practices, and support sales through solutioning and client-facing technical leadership.

This role involves designing and implementing document intelligence workflows using large language models (LLMs), focusing on automation in financial technology products, and providing mentorship to team members.