Top Machine Learning Engineer Jobs

Lead definition and implementation of the companys ML strategy and infrastructure. Build end-to-end production ML systems (data pipelines, training, evaluation, serving), own data strategy and feedback loops, integrate ML with product/backend, write production-quality code, and recruit/mentor the ML team as it scales.

Design, build, and deploy scalable GenAI/ML applications on AWS. Advise customers, gather requirements, lead model training and deployment, optimize performance, manage risks, and mentor colleagues while producing reusable artifacts.

The Machine Learning Engineer will develop machine learning models, optimize processes, and collaborate with engineers to enhance data analysis and automation.

As an ML Engineer, you'll build and deploy scalable ML systems, optimize models, and collaborate with teams to improve content across platforms.

As an ML Engineer Intern, you will build and deploy ML models, design scalable infrastructure, and collaborate with data science teams in a fast-paced environment.

Lead development of scalable ML infrastructure, focusing on compute for simulation, data labeling, and data generation. Collaborate with ML engineers, set technical roadmaps, ensure system reliability, and research advanced computing techniques.

The Senior ML Infrastructure Engineer will design, implement, and optimize computing platforms for simulation workflows, ensuring high reliability and performance. Responsibilities include leading technical decisions, collaborating with ML engineers, and enhancing system efficiency.

Lead hands-on technical leadership in machine learning engineering, mentor peers, oversee infrastructure delivery, and foster innovation in AI/ML solutions at Xometry.

Develop and optimize computer vision models for drones, improve ML pipelines, collaborate on R&D, and tackle advanced technical challenges.

As a Staff Machine Learning Engineer, optimize card pricing models, lead ML lifecycle, collaborate with experts, and enhance predictive features.

Design and deploy machine learning models for creating HD maps, utilizing advanced ML techniques and collaborating with other teams to deliver reliable solutions.

This role involves advancing autonomous vehicle simulations using Generative AI technologies, managing the lifecycle of product innovations, and collaborating in an ML engineering team.

Design and deploy machine learning models for HD map automation, collaborating with teams on building scalable mapping solutions.

As a Machine Learning Engineer, you will design core platforms for autonomous agents, engineer data systems, build tools, and enhance product experience while collaborating with data scientists to deploy advanced models.

Seeking a Senior AI/ML Engineer with expertise in machine learning frameworks to support a U.S. Government customer on critical software systems.

Design and maintain multilingual datasets, develop data pipelines, implement quality filters, and analyze dataset biases while collaborating with researchers.

Optimize inference latency and throughput for large-scale ML models, collaborating on performance tuning, and building inference-serving systems.

The ML Engineer will optimize large-scale model training pipelines, improve distributed training strategies, build robust infrastructure, and collaborate on training techniques and performance metrics.

Design and implement knowledge distillation pipelines, optimize training and inference performance, and collaborate with research on production-ready ML models.

The Senior Staff Machine Learning Engineer will architect ML systems for search and recommendations, mentor engineers, and collaborate across teams to enhance content discovery on Patreon.

The Machine Learning Engineer will develop and innovate ML models and their infrastructure, collaborate, mentor, and take ownership of impactful projects.

As a Research Engineer, you'll work on pretraining, scaling, post-training, and deployment of AI models, improving infrastructure and performance.

The Applied Machine Learning Engineer will develop machine learning models, transform data science prototypes, and build efficient self-learning applications for greenhouse operations.

The Machine Learning Engineer will develop AI capabilities by creating algorithms for data analysis, enhance data processing methods, and support military intelligence applications.

The On-Device Machine Learning Engineer will optimize and deploy ML models on consumer hardware, enhancing performance while ensuring privacy and reliability. Responsibilities include model optimization, lifecycle management, and collaboration with product teams to achieve high user experience benchmarks.