Top Machine Learning Engineer Jobs

Design and implement AI/ML solutions for healthcare, collaborating with teams to translate complex requirements, deploy models, and process large datasets.

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

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.

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.

As a Lead AI/ML Engineer, you will design and implement AI solutions within healthcare, drive technical direction, mentor engineers, and ensure integration into workflows to improve care delivery.

The AI/ML Engineer will implement RAG pipelines, integrate LLMs, maintain REST APIs, and design Postgres schemas for enhanced data management.

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.

The AI/ML Engineer will develop and maintain RAG pipelines, integrate LLMs into applications, manage REST APIs, and enhance Postgres schemas while requiring active TS/SCI security clearance.

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.

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

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.

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.

Develop and deploy AI/ML models in the pharmacy domain, focusing on Generative AI technologies and collaborating with operations and capability teams.

The AI/ML Engineer will develop and deploy AI solutions using Generative AI technologies, focusing on LLMs and frameworks like LangGraph and LangChain. Responsibilities include building APIs, deploying ML models on cloud platforms, optimizing solutions, and collaborating with stakeholders.

The AI/ML Engineer will architect solutions leveraging NLP and ML, manage cloud deployments, and enhance workflows for efficiency.

As a Staff Machine Learning Engineer, lead teams in designing AI solutions, managing projects, and interfacing with clients while ensuring technical excellence and operational effectiveness.

Lead the development of automated ML-driven map reconstruction systems. Architect and implement pipelines to validate and maintain map primitives, ensuring reliability across large-scale deployments.

Lead the design and advancement of AI platform infrastructure, focusing on distributed training, efficiency, and optimization of ML models. Collaborate with teams and guide architectural decisions.

Lead the design and implementation of AI/ML systems, collaborating with cross-functional teams to deliver scalable solutions and mentor engineers.

Lead end-to-end ML projects, architect scalable systems, drive MLOps excellence, mentor engineers, and collaborate with product and data teams to deliver ML solutions.

Responsible for shipping production ML systems, designing robust architectures, maintaining data pipelines, and collaborating to translate product goals into ML solutions.

The Senior Machine Learning Engineer will design, build, and deploy AI agents at scale, enhancing Dropbox Dash's search and organization features. Requires extensive ML experience and proficiency in Python and ML libraries.

Lead design and implementation of LLM observability features: prototype and scale product capabilities for tracing, evaluating, and debugging generative AI systems. Work cross-functionally to influence architecture, mentor engineers, prioritize customer pain points, and drive product and engineering decisions for reliable, high-performance AI observability.

As a Lead Machine Learning Engineer, you'll design, build, and implement ML applications, collaborating with agile teams and focusing on optimizing systems at scale.

The Senior Lead Machine Learning Engineer will design, develop, and implement machine learning systems, collaborating with teams to solve business problems using machine learning applications.