Top AI & Machine Learning Jobs

Lead software engineering, DevOps, cloud platform, and applied AI efforts. Build platform architecture, CI/CD, infrastructure-as-code, observability, MLOps, and OTA firmware update systems. Recruit and mentor engineers, manage vendors and budgets, partner with embedded teams, and deliver scalable AI/ML and cloud solutions to improve operations and product outcomes.

Develop scalable software and data pipelines for clinical data, applying statistical computing, machine learning, and simulation. Build and maintain large-scale databases and cloud infrastructure, translate research algorithms into production code, gather requirements, document technical work, and present results to internal and client stakeholders.

Open application inviting candidates to propose a role at Valency. Send resume/bio, a short note describing your fit, and work samples. The small hybrid team builds AI-first research and knowledge infrastructure; successful candidates are systems thinkers comfortable with ambiguity who enjoy early-stage product work.

Build and ship agent-driven internal products and Slack interfaces, extend and steward the Centaur runtime and agent CLIs, integrate harnesses and developer workflows, and maintain open-source community-facing docs, triage, and PRs to improve firm operations and developer extensibility.

Pioneering machine learning solutions for the defense sector, developing and deploying production-grade ML models, tackling complex data challenges, and collaborating with engineers.

Build and ship end-to-end features and systems for an AI-native commercial insurance broker. Design backend architecture, implement durable workflow orchestration, productionize agentic LLM applications, and build RAG/search pipelines. Work directly with founders, brokers, and customers to iterate and deploy AI-driven automation and customer-facing products.

Develop and scale machine learning training systems for robotics data, optimize training pipelines, and collaborate with ML researchers to enhance autonomy models.

The Lead AI Engineer will design and develop scalable AI/ML solutions, focusing on automation, document retrieval, and decision-making processes while mentoring team members and collaborating with cross-functional teams.

Architect and manage ML pipelines for training and deployment on cloud platforms, automate CI/CD, and ensure system performance and availability.

Customer-facing senior engineer who deploys and operates an LLM-powered AI SRE product in enterprise environments. Own end-to-end implementations, integrations (observability, ITSM, ticketing, collaboration), migrations from incumbent AIOps platforms, incident response and RCA, alert normalization, and production-grade AI workflow design while driving customer outcomes and product feedback.