Top Machine Learning Engineer Jobs

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

The Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.

Lead design and implementation of enterprise-grade AI systems, architect AI infrastructure, and drive technical strategy for AI-powered products primarily for military applications.

Lead technical direction on projects, mentor engineering teams, and build scheduling tools and forecasting interfaces for support agents. Collaborate with product and design teams to convert vague problems into technical solutions.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

The role involves designing and optimizing large-scale multimodal AI models, conducting applied research, and collaborating with cross-functional teams to deliver impactful member value at WHOOP.

As a Staff Machine Learning Engineer, you will design and implement infrastructure for AI workloads, collaborate on GPU cluster performance, and write scalable code while mentoring colleagues.

Design, implement, and deploy ML inference engines on custom FPGA/ASIC hardware. Perform HW/SW co-design with traders and researchers, optimize neural networks for low latency, and build quantization/compression tools to translate ML frameworks to RTL for rapid production deployment.

Lead the design and deployment of machine learning models for personalized navigation and recommendations, managing projects end-to-end with a focus on user-centric solutions.

Design and deploy ML models for fraud detection, develop data pipelines, partner with teams to ensure effective fraud prevention, and enhance detection accuracy.

Lead AI ML Engineer responsible for building AI systems, ensuring model quality, and driving architecture and governance standards while collaborating cross-functionally.

The role involves developing an AI agent platform, building ML models, and enhancing user experiences with advanced algorithms. Collaboration and fast-paced execution are key.

As a Machine Learning Engineer, you will enhance internal libraries for deep learning, collaborate with researchers, and optimize workflows for cost savings.

Develop and implement AI/ML strategies for healthcare, build models, design experiments, collaborate with teams, and ensure compliance with AI policies.

Lead the design and development of AI/ML models for healthcare. Collaborate with business partners and other teams to ensure high-quality execution and adherence to architectural principles.

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 Machine Learning Engineer Senior will design and develop ML algorithms to enhance analytics and decision-making, optimizing model performance, and ensuring reliability and data quality.

Lead the development of ranking and relevance models, design ML systems for patient-provider matching, and mentor junior team members.

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.

Partner with CV researchers to productionize models, optimize training and real-time inference performance, design reusable abstractions, and collaborate with MLOps/backend teams to evolve the CV inference platform for scale and reliability.

Design, build, and scale production ML systems (including LLMs) to automate customer support and compliance workflows. Lead technical roadmaps, write high-quality Python code, mentor engineers, ensure secure, scalable architectures, and resolve complex reliability issues.

Build and own full-stack UX and backend systems for the ML lifecycle: design architecture, integrations, observability, CI/CD, and production frontend/backends. Lead technical initiatives, mentor engineers, and collaborate across teams to scale ML platform capabilities.

As a Machine Learning Engineer, you will design algorithms, maintain data pipelines, collaborate on software deployment, and ensure the scalability of ML systems.

As a Machine Learning Engineer, you will design and optimize algorithms, manage ML data pipelines, and ensure system scalability while collaborating with teams to enhance software deployment.

The Staff Machine Learning Engineer will architect and optimize data infrastructure for multimodal AI models in oncology, focusing on data management and processing pipelines.