Top Machine Learning Engineer Jobs

Design and scale ML platform infrastructure for large 3D datasets: build training pipelines, deploy generative models, optimize ML lifecycle, ensure cloud-native reliability and observability, and collaborate across engineering.

Lead development of advanced recommendation systems, driving ML innovation, maintaining ML pipelines, and collaborating across teams to enhance user engagement.

As a Senior Machine Learning Engineer, you will design and implement machine learning models, collaborate with Agile teams, and ensure the performance and scalability of solutions.

As a Machine Learning Engineer, you will develop, implement and deploy ML models, collaborate with teams, and ensure model performance while working with healthcare datasets.

Lead the strategy and development of state-of-the-art end-to-end autonomous driving research, optimizing ML models and collaborating across teams to influence technical decisions.

The intern will prototype control/estimation algorithms, collaborate on algorithm development for vehicle control, and demonstrate impact in simulation or on prototypes.

Develop and optimize machine learning models for financial and operational workflows at Netflix, ensuring model reliability and integration with studio applications.

Build and deploy LLM-based chatbots and machine learning models, integrate agents with enterprise databases and APIs, perform data preprocessing and model evaluation, automate data pipelines, and collaborate with internal teams and clients.

The Staff AI/ML Engineer will lead AI product development, ensure system health, and collaborate with teams on product features while maintaining security and compliance.

Own deployment, optimization, and maintenance of production TTS systems. Implement post-training and inference techniques, ensure low-latency real-time audio pipelines, maintain scalable infrastructure, and collaborate on A/B testing and iterative improvements for enterprise voice services.

The role involves implementing features for ML data processing, developing workflows for model training and deployment, and supporting ML pipeline operations.

The role involves leading the design and implementation of multi-stage ML training systems for autonomous vehicles, optimizing training processes and collaborating with various teams.

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.