Top Remote Machine Learning Engineer Jobs

The Lead AI/ML Engineer will develop AI and ML strategies in healthcare, manage teams, and ensure quality delivery of AI solutions.

The Staff Machine Learning Engineer will lead the development of AI solutions, ensure project delivery, and manage technical teams while interfacing with customers. Responsibilities include designing data pipelines, overseeing machine learning model development, and facilitating customer engagement.

The Staff Machine Learning Engineer will lead ML initiatives, partnering with multiple teams to enhance customer support through AI-driven solutions, focusing on conversational agents and research in chatbot architectures.

Lead design, development, and production deployment of AI/ML solutions and conversational chatbot platforms. Own end-to-end implementation, MLOps/CI-CD, containerized deployments, solution architecture, security and governance, mentor engineers, and collaborate with product, enterprise architecture, and vendors to deliver scalable, monitored AI systems.

Lead technical design and delivery of production AI/ML and GenAI solutions (RAG, LLMs, agents). Build, tune, deploy, and monitor models and APIs, own MLOps practices, operate cloud AI workloads, ensure software quality and responsible AI, and partner with cross-functional stakeholders while mentoring engineers.

Design, build, and deploy production-grade ML and AI solutions for behavioral health. Architect end-to-end MLOps pipelines, optimize and monitor models in production, evaluate emerging AI trends, collaborate cross-functionally, and provide technical leadership and mentorship to engineering teams while ensuring responsible, scalable, and secure AI deployments.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

Design, build, test, and deploy production AI/ML solutions and full‑stack applications (React/Next.js, Python, PostgreSQL). Integrate LLMs and agentic AI frameworks, develop backend services/APIs, collaborate cross-functionally, and optimize reliability and performance within regulated clinical workflows.

Lead design, development, and deployment of production-grade, large-scale ML systems. Influence ML strategy, integrate models with platform and data infrastructure, mentor engineers, communicate results to stakeholders, and mature ML infrastructure and abstractions across teams.

Lead design, development, and deployment of large-scale production ML systems and platform strategy. Research and prototype ML and big-data technologies, integrate ML services across the org, mentor engineers and data scientists, and communicate complex ML solutions to technical and non-technical stakeholders.

As a Senior AI/ML Engineer, design and deploy AI solutions using Generative AI techniques within cloud-native architectures, mentoring junior engineers and ensuring compliance with ethical standards.

As a Lead AI/ML Engineer, you will design and implement scalable AI solutions, mentor teams, and integrate cutting-edge technologies to improve healthcare applications.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

Lead development and production of underwriting and credit decisioning models across Cash App Borrow and Afterpay. Own full modeling lifecycle: problem formulation, feature engineering, training, calibration, experimentation, deployment, monitoring, and iteration. Build decision frameworks, agentic engineering workflows, and collaborate with cross-functional partners to align model behavior with business and regulatory goals.

Develop and deploy machine learning solutions for autonomous vehicles, mentoring engineers and collaborating on model implementations.

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

Lead the design, implementation, and deployment of scalable ML infrastructure for autonomous driving. Drive technical projects, mentor others, and collaborate with teams to enhance ML workflows.

The Senior AI/ML Engineer will enhance developer productivity by improving Python workflows, leading projects, mentoring engineers, and driving best practices.

Lead and develop advanced machine learning models for autonomous driving, collaborating with teams, and driving technical initiatives in a hybrid work environment.

Senior individual contributor building and maintaining underwriting and credit decisioning ML systems for Cash App Borrow and Afterpay. Responsibilities include feature engineering, model training, calibration, experimentation, deployment, monitoring, and portfolio-level analysis. Collaborate with cross-functional teams to align models with business and regulatory goals and develop AI-native engineering workflows and governance for reliable, auditable model development.

Design, build, and deploy scalable AI/ML models and pipelines for consumer healthcare. Develop production code (Python/Java/Scala), automate infrastructure (Terraform, Kubernetes), validate model performance, integrate cloud services (Azure/AWS), and collaborate cross-functionally to monitor and document enterprise-scale AI solutions.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

Develop large-scale Foundation Models for Autonomous Driving & Robotics, collaborating with teams, optimizing model performance, and mentoring junior members.

Design, build, and deploy enterprise-scale generative AI and LLM applications, agentic workflows, and RAG pipelines. Develop full-stack solutions using React/Next.js, Python/Node.js, and PostgreSQL; integrate vector databases and optimize retrieval; lead technical design, mentor engineers, and ensure responsible AI deployment and scalability.

As a Senior AI/ML Engineer, you will design and build end-to-end ML systems, manage ML lifecycle workflows, and ensure compliance with AI standards within the healthcare sector.