Top Machine Learning Engineer Jobs

As a Principal Machine Learning Engineer, you'll develop advanced ML solutions using LLMs and Knowledge Graphs, leading teams and driving innovation in AI technologies for improved customer experiences.

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

The role involves designing and deploying AI systems for a SaaS platform, focused on operational automation using machine learning models and APIs.

Design, train, and deploy predictive models for adversarial systems while building high-performance ML infrastructure and contributing to research and open-source projects.

The Machine Learning Engineer will develop and deploy software for government projects, build data pipelines, and manage the data lifecycle.

Lead the development of machine learning models for autonomous vehicles, improve data systems, and collaborate across teams to enhance technology and performance.

The role involves optimizing Small Language Models for NVIDIA's G-Assist, enhancing context-aware features, and ensuring system performance while collaborating with engineering and product teams.

As an AI and ML Engineer, you will develop AI/ML solutions for object identification, collaborate with teams, and maintain models for data processing.

As a Staff ML Infra Engineer, you will develop and deploy offboard machine learning solutions for autonomous vehicles, ensuring model integration and performance across teams. You'll build ML infrastructure, implement CI/CD pipelines, support data curation, and mentor engineers.

Designs, builds, and optimizes production data and model pipelines; applies statistical and ML methods to create automated predictive systems; partners with data scientists and stakeholders for feature and data readiness; implements model monitoring, diagnoses issues, and contributes to analytics initiatives across business domains.

Design and develop AI conversational agents and intelligent search systems. Collaborate on scalable AI solutions, mentor team members, and enhance existing products.

The role involves designing AI agents, building intelligent search capabilities, collaborating on scalable solutions, and delivering high-quality products while mentoring colleagues.

Design, build, and optimize scalable ML infrastructure for LLMs, collaborating with cross-functional teams to enhance ML workflows and algorithms.

The Senior Machine Learning Engineer will develop foundational models for recommendations, mentor engineers, and collaborate on improving user experiences with machine learning.

Design, build, and scale ML platform components including training pipelines, serving, feature stores, and monitoring. Lead projects from design to deployment, improve system reliability and observability, mentor engineers, and collaborate with data science and infrastructure teams to enable reproducible production ML workflows.

The role involves building and optimizing a machine learning and simulation platform, supporting MLOps, model deployment, and infrastructure modernization, while mentoring engineers.

Design, build, and deploy production GenAI solutions (including chatbots) for finance use cases. Process structured and unstructured data, implement RAG pipelines, vector DBs, text-to-SQL, integrate with cloud/MLOps, and collaborate with stakeholders and engineering teams.

The Principal AI Engineer at OutSystems will lead the development of AI systems, collaborate cross-functionally, and mentor other AI engineers in building and deploying scalable AI solutions.

Design and deploy machine learning models for personalized recommendations and search on Zillow's platforms. Collaborate with cross-functional teams to enhance user experience.

Design, build, deploy, and maintain custom and third-party ML models and MLOps pipelines. Collaborate with cross-functional teams to integrate models into production, ensure data quality, monitor performance, and optimize for scalability and reliability.

Design, train, test, deploy, and maintain machine learning models for DoD missions. Collaborate with data engineers, scientists, and product owners to implement deep learning, computer vision, and generative AI solutions, manage data/model pipelines, and resolve client problems.

As an AI and ML Engineer, you'll develop secure, scalable AI solutions, enhance data pipelines, and operationalize ML models in an Agile team environment.

Develop and operationalize secure AI solutions, collaborate with cross-functional teams, and enhance AI-driven platforms for mission-critical capabilities.

As an AI and ML Engineer, you will develop and deploy AI solutions, collaborating across teams to optimize models and algorithms for national security applications.

The role involves building machine learning systems for Radar's products, focusing on core ML infrastructure, anomaly detection, geolocation, and collaboration with customers.