Top AI Engineer Jobs

Translate multi-modal AI research into 0-1 products: design and run ML experiments, build scalable training and evaluation infrastructure, implement MLOps and data pipelines, deploy models, and use AI code tooling to move experiments to production MVPs.

Design, build, and operate production LLM-driven agents that crawl, extract, and verify web evidence to enrich business identities. Own classification, discovery, linkage, risk scoring, shared agent infrastructure, model/tool selection, prompt engineering, eval methodology, and cost/latency optimizations for real-time enrichment pipelines.

Develop and optimize AI pipelines for workflow intelligence, experiment with models, and collaborate to integrate AI systems into workflows.

Design and operate cloud network infrastructure on Azure and AWS, build AI platforms, oversee infrastructure-as-code, and ensure security compliance.

As a Senior Staff Applied AI Engineer at Databricks, you will design and build retrieval systems, optimize search for both LLMs and humans, and lead technical direction and team growth.

The AI Engineer IV will lead the development and implementation of AI systems, influence architecture decisions, mentor team members, and ensure best practices in a hybrid work environment.

As a Senior AI Engineer at Via, you will lead the development of AI products, collaborate with partners, design scalable systems, and shape the technical culture of a new team.

The AI Engineer will analyze business processes for automation opportunities, design and maintain RPA solutions, and develop Intelligent Document Processing systems while collaborating with stakeholders and ensuring reliability of solutions.

Design, develop, and implement AI/ML models, manage AI solutions on cloud platforms, and collaborate with teams to optimize models.

As a Data/AI Engineer Intern, responsibilities include data analysis using AI tools, model development, and collaborating with stakeholders to address business challenges.

Develop AI-enabled tax solutions by enhancing the TRAM system, improving data pipelines, and collaborating with tax experts for model refinement.

The AI Engineer will develop AI/ML solutions for investment analysis, design applications, optimize models, and work with large datasets in healthcare and finance contexts.

The AI Engineer will design and build AI systems using LLMs, develop agent workflows, implement APIs, and collaborate with teams to optimize AI applications.

The Senior Applied AI Engineer will build production-grade AI systems, collaborating with cross-functional teams to ensure impactful care solutions while leading engineering initiatives and mentoring team members.

The Senior AI/ML Engineer will design, develop, and deploy language models for African languages, focusing on NLP applications and cultural context.

Lead development and deployment of AI-first systems: build generative and discriminative models, enable multimodal behavior classification from mobile signals, define prompting and benchmarking standards, own ML tooling and SDLC, and partner with Product and Engineering on the AI roadmap.

As an Applied AI Engineer at Luminai, you will design experiments, optimize machine learning models, and enhance AI platforms for healthcare automation.

As an AI Engineer, you'll build and deploy AI applications, integrate LLM systems, and work with complex regulatory datasets to enhance the Redica platform.

As an Agentic AI Developer, you will design production-grade AI agents for supply chain operations, focusing on decision-making, integration with enterprise systems, and ensuring safety and compliance in autonomous workflows.

As a Senior AI Engineer, you will develop backend systems and AI applications for Clarium's healthcare supply chain platform, ensuring alignment with real-world workflows and critical system components.

As an AI Engineer at Clarium, you will build and maintain data enrichment pipelines, design classification workflows, analyze datasets, and ensure data quality, primarily using Python and SQL, and work closely with senior engineers and data scientists.

Design and implement AI solutions, focusing on data pipelines, workflow automation, and ensuring security and governance in a production environment. Collaborate to create reliable, scalable models and optimize enterprise data integration.

Build, deploy, and maintain production AI agents for scientific R&D. Work directly with customers to prototype, integrate, troubleshoot, and iterate on agent architectures, prompting, tooling, and evaluation to deliver measurable scientific and operational impact.

Lead the design and development of advanced AI agents for cybersecurity, focusing on real-time decision-making and adaptive threat responses, while mentoring teams and collaborating across functions.

The role involves designing and deploying generative AI solutions, collaborating with teams, ensuring security and compliance, and guiding architectural decisions for AI initiatives.