Top AI & Machine Learning Jobs

Embed with enterprise customers to deliver on-prem and air-gapped deployments, diagnose and remediate production issues, build customer-specific extensions, upstream solutions into product, and codify playbooks to scale field engineering.

The Senior MicroStrategy Developer will build dashboards, provide technical guidance, align project requirements, and oversee capacity planning while optimizing performance.

Join a start-up as a Data Platform Engineer, responsible for dimensional modeling and data warehousing using Django/Python. Implement designs and impact software direction.

Lead the development of appraisal and pricing capabilities using data science to automate valuation decisions. Collaborate across teams for insights into pricing and operational strategies.

Build, refine, and scale production agent systems: multi-step tool-using agents, memory systems, proactive agents, and evaluation frameworks. Ensure fast, predictable, traceable behavior and uptime while working across infra, frontend, and product.

Lead end-to-end perception projects from design to production, define technical approaches, mentor engineers, set engineering quality standards, and collaborate with Platform and Product to scale models across cloud and edge using MLOps pipelines.

Lead and build AI-native, agentic applications and the engineering platform; define agentic development patterns, CI/CD, IaC, observability, and security practices; mentor and recruit engineers; prototype and productionize solutions for field-based operational users.

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

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.

Develop and test quantitative trading models using statistical and machine-learning methods on large financial datasets. Perform research-driven analysis, build predictive models, and communicate findings to integrate into strategy frameworks.