Top Hybrid Machine Learning Engineer Jobs

Design, build, and manage large-scale search and content recommendation systems using machine learning and personalization techniques. Collaborate with content, product, and business teams to define success metrics, drive AI product improvements, and maximize content value and user impact.

Build and maintain production AI/ML models and pipelines for an NDR platform; develop scalable, secure backend services; optimize detection algorithms and reduce false positives; integrate ML features into product architecture; mentor engineers; participate in code reviews, technical strategy, and documentation; operate cloud-native, containerized services and manage infrastructure as code.

Lead the AI & Analytics stream to design, build, and deploy predictive and prescriptive ML models, integrate analytics into enterprise platforms (Salesforce, ServiceNow), automate root-cause and log analysis, translate stakeholder needs into production solutions, and manage analytics projects end-to-end while communicating results to technical and executive partners.

Design, implement, and optimize machine learning and deep learning models; preprocess and analyze large datasets; integrate models into production; monitor performance and troubleshoot; collaborate with engineers, data scientists, and stakeholders; stay current with ML/AI advances.

The AI Intern supports Hoosier Energy in leveraging artificial intelligence for efficiency by developing AI models, preparing datasets, and ensuring compliance with data governance.

Embed with strategic customers to own end-to-end delivery of robotics/egocentric data products: translate requirements, sequence and QA deliveries, triage technical issues, and feed recurring needs into the data-engine and annotation roadmaps to improve model performance.

Own and ship full-stack features across frontend, backend, and data layers. Extend a Brand Knowledge Graph in Neo4j, build predictive optimization and measurement systems, design LLM orchestration and AI integrations to minimize calls, and deliver client-facing demos and QA. Translate complex data and models into actionable insights and maintain integrations and tracking infrastructure.

Own end-to-end matching and ranking systems for out-of-home advertising: design candidate generation and re-ranking models, build and manage data warehouse and pipelines, implement evaluation and monitoring, publish low-latency ranking APIs, and maintain model observability and retraining workflows.

Conduct R&D on AI/ML and machine translation for SIGINT and cybersecurity applications. Build research prototypes, evaluate and enhance MT tools and text-processing pipelines, and implement containerized solutions. Resolve complex AI technical problems and collaborate with senior technical staff.

Design, train, and deploy multimodal machine learning systems that fuse 3D/vision, simulation, tabular, and text data. Own end-to-end model lifecycle from architecture and training to evaluation, production deployment, and monitoring, and build agentic workflows and retrieval/embedding capabilities to support underwriting and mitigation decisions.