Top AI & Machine Learning Jobs

Develop and evaluate real-time machine learning algorithms for audio processing applications, including voice pickup and hearing augmentation. Prototype solutions, integrate them into existing platforms, curate internal resources, present findings, and contribute to customer products, patents, and research publications. The role involves collaboration across machine learning, digital signal processing, software engineering, and psychoacoustics.

Serve as the CEO's operational right hand, managing executive calendar, travel, communications, contracts, and cross-functional project execution. Maintain dashboards, SOPs, and documentation, coordinate leadership communication and recruiting, remove blockers, recommend process improvements, and represent the company at meetings and events to increase operational efficiency and CEO focus on strategy and customers.

Build and ship AI-powered products end-to-end, design architectures for retrieval, memory, and agentic systems, and implement evaluation pipelines. Work in small, ambiguous startup teams, communicate effectively, and demonstrate strong software engineering fundamentals alongside deep LLM and agentic systems expertise.

Conduct foundational and applied ML research on AI well-being and moral status, design and run experiments (including tooling/infrastructure), collaborate with external researchers, and publish papers, blog posts, and talks to inform AI developers, policymakers, and the public.

The Customer Solutions Engineer manages system integrations, provides technical support, troubleshoots complex issues, and optimizes operational systems while collaborating with clients.

Design and ship production LLM features for a SaaS product: build customer intelligence from recordings and text, prioritize testimonials using metadata, create AI-powered surveys/interviews, iterate via research, prototyping, deployment, and evaluation. Own technical decisions and deliver measurable outcomes working closely with engineering leadership and customers.

Lead and deliver enterprise AI solutions from design to production, define Databricks-based technical standards, establish MLOps/CI-CD and monitoring, manage multidisciplinary data teams, partner with executives to prioritize AI roadmap, oversee budgeting and regulatory compliance in a financial services environment.

Own product analytics and data science for a business-critical product area. Develop production-ready churn, resurrection, and targeting models; define metrics; analyze experiments; apply causal inference; and deliver actionable recommendations with quantified business opportunities. Partner closely with Product, Engineering, Design, and Growth teams while contributing to experimentation methodology, standards, and tooling.

Lead BlackLine's enterprise AI transformation: define strategy, governance, and measurable outcomes; build and run AI program and team; partner with business and IT to design, deploy, and adopt AI agents and automation; enforce responsible AI, data governance, and compliance; report progress to CIO and senior leadership.

Lead Datadog AI Research’s post-training and autonomous-agent research team. Set technical direction across reinforcement learning, simulated environments, synthetic data generation, evaluation, and agent training. Mentor researchers and research engineers while remaining hands-on in experimentation, model development, and technical problem-solving. Collaborate with Product and Engineering to commercialize research advances, contribute to publications and conferences, and open-source model artifacts and benchmarks.