Top Machine Learning Engineer Jobs

As a PhD intern, you will research generative models, collaborate on simulations, and contribute to high fidelity sensor data evaluation.

Lead end-to-end design and delivery of Stripe Assistant's ML and agent architecture. Improve answer quality, safety, and execution for high-trust actions using LLMs, RAG, fine-tuning, and agent orchestration. Set SLOs, build evaluation and benchmarking pipelines, optimize latency/cost/reliability, and mentor engineers while collaborating cross-functionally to ship secure, observable, and scalable AI-driven features.

Develop and implement advanced machine learning models for autonomous driving, focusing on deep learning, perception, and real-time performance optimization.

Design and implement workflows using large language models to automate processes, lead integration efforts, and evaluate new technologies.

Design and implement production-grade ML systems for ICS/OT cybersecurity, build and optimize models (including NLP/LLMs), develop data pipelines and MLOps workflows, collaborate with data teams to deploy and monitor models in cloud and on-prem containerized environments, and troubleshoot production performance and resource issues.

Develop and maintain ML pipelines for entity classification; collaborate with data scientists; implement monitoring frameworks and improve data workflows.

The AI and ML Engineer will develop and maintain AI/ML models, collaborate with teams to deliver solutions for national security, and apply algorithms.

As an ML research engineer, you will develop systems using language models, curate datasets, set evaluation metrics, and scale semantic search processes.

Lead design and deployment of scalable ML platforms and tools, manage complex technical projects, mentor junior engineers, and collaborate across teams to enhance autonomous driving systems.

The co-op involves developing DSP and ML algorithms focused on room acoustics, conducting acoustic simulations, and researching audio signal processing methods.

The Senior Machine Learning Platform Engineer will build foundational components for ML models, mentor junior engineers, and optimize streaming pipelines. Responsibilities include enhancing ML infrastructure and ensuring data quality.

As a Senior Machine Learning Engineer, you'll design, develop, and implement scalable ML applications, collaborate with cross-functional teams, and optimize models while ensuring high performance and responsible AI practices.

The Senior Machine Learning Engineer will architect the ML infrastructure, productionize models, maintain data platforms, and ensure system health, collaborating closely with data scientists and data engineers.

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

As a Machine Learning Engineer, you'll evaluate neural network quality, coordinate with researchers, manage experiments, and report results to streamline AI software development.

Design and deploy AI-powered solutions using ML techniques. Collaborate with teams to develop models and optimize architectural decisions.

The Machine Learning Engineer will develop and test GenAI architectures, fine-tune LLMs, apply ML algorithms, and contribute to architectural design in a collaborative environment.

Design and build state-of-the-art speech and ML models, convert research into B2B products and APIs, optimize and scale production pipelines, collaborate cross-functionally, and maintain deployed models.

Machine Learning Engineers will apply machine learning techniques to enhance products and services by developing, implementing, and optimizing machine learning models in collaboration with cross-functional teams.

Lead ML strategy and standards as a senior individual contributor: define ML infrastructure, tooling, and lifecycle processes; establish monitoring and feature patterns; partner across platform, data, and product teams; mentor data scientists and ML engineers to scale reliable production ML systems.

Seeking a Machine Learning Engineer to apply AI technologies in high frequency trading, focusing on automation and collaboration with AI research.

Seeking a Senior Applied Machine Learning Engineer to develop and integrate AI solutions for procurement optimization in construction, enhancing decision-making and insights.

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 role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.