Top Machine Learning Engineer Jobs

As a Backend ML Pricing Software Engineer, you'll design and implement core pricing services, enhance APIs, and collaborate with data scientists to optimize pricing models for Opendoor.

Design and implement core pricing services, improve APIs, build robust model-serving pipelines, and mentor engineers, focusing on SQL databases and production systems.

Lead design and implementation of MLOps platforms for pricing: productionize models, own end-to-end pipelines (ingest, training, deployment, monitoring), optimize data access and SQL, automate retraining and releases, improve reliability and observability, mentor engineers, and participate in on-call incident response.

As a Staff Machine Learning Engineer, you'll enhance credit products through advanced modeling techniques, data analysis, and ML operations, supporting robust decision-making processes.

As a Staff Machine Learning Engineer, you will enhance credit modeling, manage full credit modeling stacks, and support innovations within regulated banking frameworks.

The Staff Machine Learning Engineer will develop machine learning models to enhance advertising strategies, improving relevance, ranking and customer engagement for Chewy's sponsored ads.

As a Machine Learning Engineer at True Anomaly, you'll design and develop ML capabilities, assist with model development, and support data pipelines while collaborating with senior engineers in a mission-driven environment.

Develop and deploy reinforcement learning, optimization, and sequential decision-making systems for satellite constellation planning. Build high-fidelity simulation and evaluation environments, create multi-objective optimization pipelines, train and productionize ML models with modern DevOps, and collaborate with aerospace engineers and operators to translate mission requirements into operational AI systems.

As a Senior AI/ML Engineer, you will design and build end-to-end ML systems, manage ML lifecycle workflows, and ensure compliance with AI standards within the healthcare sector.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

The Principal AI/ML Engineer will lead the AV ML Infra team, overseeing scalable ML infrastructure, project ownership, collaboration, and team mentorship in AI and ML innovation at GM.

As a Principal Machine Learning Engineer at Zscaler, you will lead AI/ML projects, optimize systems, and collaborate on cybersecurity solutions while mentoring engineers.

The AI/ML Engineer will implement and maintain RAG pipelines, integrate LLMs with APIs, develop REST APIs, and refine Postgres schemas, requiring a TS/SCI security clearance.

As an Applied Machine Learning Engineer, you will develop AI and ML models to improve healthcare outcomes. Collaborate with teams to implement and optimize machine learning techniques and algorithms.

Lead end-to-end design, implementation, deployment, and operation of production AI/ML-enabled full-stack applications. Build LLM-powered features, design scalable backend services and data models, deploy on Azure, implement CI/CD and observability, and mentor engineers while ensuring secure, compliant integration into clinical workflows.

Design, build, deploy, and maintain production machine learning models and pipelines at scale. Collaborate in cross-functional Agile teams to architect ML systems, automate testing and CI/CD, monitor model performance, and apply responsible and explainable AI practices. Leverage cloud platforms and distributed computing to optimize model training and serving.

As an AI Engineer, you will develop and optimize AI systems for legal tasks, work on integrating models, and establish evaluation frameworks to enhance decision-making capabilities in complex legal workflows.

Design, train, optimize, and deploy efficient on-device ML models (audio and vision) for resource-constrained products; maintain Ambiq ADKs; port and optimize customer models; apply model-efficiency techniques; produce customer-facing demos, docs, and benchmarks.

The AI/ML Engineer designs and develops AI solutions, optimizes models, manages data flow for deployment, and conducts data analysis to enhance operational outcomes for mission operations.

Design and develop AI solutions, manage data flow for AI deployment, optimize models, and conduct data analysis on large datasets for operational improvement.

As a Staff AI/ML Engineer, you'll enhance developer productivity, mentor engineers, drive best practices, and implement scalable solutions for AV tools and services.

Lead design and development of scalable, high-performance ML training infrastructure. Drive distributed training performance optimization, observability, and developer experience. Own cross-functional infrastructure initiatives, set technical direction and standards, and mentor engineers to deliver platform capabilities that support large-scale model training.

Design, implement, and optimize computer vision and deep learning algorithms for ADAS using camera feeds. Develop and validate detection, segmentation, tracking, and image-enhancement models, optimize for real-time embedded ECUs, analyze datasets, run experiments, debug defects, and integrate solutions into serial-production automotive systems.

Lead end-to-end ML and perception efforts for future sensing in autonomous vehicles: design sensor architectures, multi-modal fusion, model development, metrics, simulation-driven evaluation, system integration, and production readiness while mentoring engineers and building scalable data and training infrastructure.

Develop and evaluate ML and perception models for future sensing and autonomous driving. Work on detection, tracking, classification, sensor fusion, training pipelines, validation, robustness metrics, and integrate models into onboard systems while collaborating with cross-functional teams.