Top Senior Machine Learning Jobs

Develop and deploy lightweight machine learning models for edge AI, working on hardware integration and optimization techniques while mentoring junior engineers.

As a Senior Software Engineer, you'll build AI features focused on LLMs and RAG systems, collaborating across teams to ensure robust performance.

As a Senior Machine Learning Engineer, you will design and maintain ML systems for content recommendations, search, and spam detection, while augmenting user experience and system performance.

Lead design, development, and productionization of advanced ML models and data pipelines. Drive architecture, experimentation, validation, and best practices while mentoring ML engineers and delivering scalable, business-driving AI solutions.

Lead design, development, and deployment of advanced machine learning models and infrastructure. Own architecture, data pipelines, experimentation, validation, and team technical leadership to drive AI-driven product features and business value.

Design, develop, and deploy scalable ML software systems for healthcare. Collaborate with teams to improve products and ensure performance and reliability.

Design and develop scalable ML systems for healthcare, collaborating with teams to enhance products and maintain efficient infrastructures.

The Staff Machine Learning Engineer (Pricing) will design and deploy ML systems for pricing optimization at GoFundMe, including model development, real-time inference, and metrics evaluation while collaborating with cross-functional teams.

Lead the design, development, and implementation of advanced machine learning models, collaborating with teams to enhance services through AI/ML solutions.

Lead end-to-end ML projects for fraud detection: develop, deploy, monitor, and iterate production models and experimentation frameworks. Improve model performance, build scalable ML pipelines, collaborate with Product/Engineering/Risk, and champion testing, documentation, and model-monitoring best practices to ensure robust, high-impact solutions.

The Senior Machine Learning Engineer will design and deploy AI systems, optimize production models, and ensure efficient performance in resource-constrained environments.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

Design, implement, deploy, and monitor production-grade ML and computer vision models (CNNs, transformers, vision-language). Evaluate models, analyze data, improve robustness, support MLOps/CI-CD, and mentor junior engineers within an Agile team.

Product-oriented senior ML role to build, deploy, and operate models and ML systems (classification, extraction, entity resolution, clustering, ranking, anomaly detection, forecasting, LLM pipelines). Define datasets, labeling, evaluations, monitoring, and collaborate with engineering and product to ship production-quality training/inference pipelines and model-serving infrastructure.

Design, implement, and test scalable, low-latency ad selection systems using rule-based and ML solutions. Build and maintain microservices, observability, and metrics; translate product stories into tasks; mentor teammates; participate in on-call rotations and own domain areas.

Lead end-to-end development of detection algorithms and production ML/physics/LLM models for HVAC sensor time-series. Build evaluation harnesses, label fault sets, optimize data pipelines, and translate model outputs into actionable field insights while partnering with hardware, software, and business teams to ship reliable customer-facing features.

Design and implement backend and systems-level software for defense and intelligence, integrating signal-processing and machine-learning algorithms into real-time, field-ready systems. Collaborate in small teams to prototype, architect, and deploy extensible solutions that integrate with existing infrastructure while translating customer requirements into development priorities.

Design, prototype, and operationalize ML models and data pipelines for temporal, geospatial, and track-based mission data. Build data processing, feature engineering, containerized cloud deployments (AWS/Docker/Kubernetes), APIs, and scalable evaluation/monitoring workflows while following Agile and software engineering best practices.

The Senior Machine Learning Engineer will lead the perception stack, focusing on detection, tracking, classification, and sensor fusion for targeting systems, with responsibilities including model development and real-time optimization on embedded devices.

The Staff AI/ML Engineer will design, build, and improve AI systems for document retrieval and data extraction, work with clients, and mentor team members to establish best practices.

Build and improve AI/ML systems and data pipelines for a B2B SaaS platform; shape product and technical strategy; work with customers; mentor team members; ensure secure, robust, and scalable infrastructure.

As a Senior Software Engineer, you'll develop machine learning models and software applications, translating technical requirements into solutions while ensuring excellence in product delivery.