Top AI & Machine Learning Jobs

Anthrogen is seeking exceptional talent for an open-ended, full-time onsite role in San Francisco. Candidates may propose research directions, technical capabilities, or unusual combinations of skills relevant to frontier AI and engineered biological systems. Applicants should demonstrate exceptional work, independent judgment, curiosity beyond a specialty, and a concrete record of building, discovering, or delivering meaningful results.

Build and iterate AI systems spanning computer vision, image manipulation, video generation, and agentic data analysis. Own the full pipeline from model research and API integration through scalable web application deployment. Develop rapid MVPs using AI-assisted tools, orchestrate multiple models into autonomous workflows, and test solutions in e-commerce operations before scaling them into SaaS products.

Leads soccer analytics and data science workstreams supporting MLS competition, player relations, medical, and sporting decisions. Uses soccer, roster, tracking, financial, and performance data with statistical, AI, and machine learning methods. Evaluates roster rules, competition changes, player pathways, and sports science trends; develops KPIs, models, reporting, and recommendations for senior stakeholders. Also guides sporting data governance, technology evaluations, vendor use, and cross-functional analytics priorities.

Build full-stack AI applications for nuclear and energy-sector document analysis and verification. Responsibilities include architecting applications, implementing Retrieval-Augmented Generation systems, developing front-end and backend services, and deploying cloud infrastructure on AWS using ECS, S3, Bedrock, API Gateway, and Route 53. The role requires production software engineering experience, Docker expertise, and collaboration in a fast-paced innovation team.

Build and maintain backend services and APIs powering LangSmith’s AI observability, tracing, monitoring, and evaluation workflows. Responsibilities include architectural design, high-volume data storage and query optimization, reliability engineering, testing, monitoring, alerting, production troubleshooting, root-cause analysis, documentation, and cross-functional feature delivery.

Design, implement, and deploy production-scale machine learning models to evaluate disputes, chargebacks, and fraud likelihood. Build and manage orchestration layers for multiple models, collaborate with stakeholders to integrate partner/customer data, and improve automated and supervised decision-making for a product-focused ML environment.

Build verification and evaluation systems that allow AI agents to determine when work is complete. Develop testing environments, convert failures and human feedback into evaluation signals, improve agent context and memory delivery, and operate the agent fleet as a production system. The role spans application code, infrastructure, testing, measurement, and ambiguous problem-solving. Prior voice, model training, or product-domain experience is not required.

Develop computer-vision methods for detecting and tracking insects in behavioral-assay videos. Build labeled datasets, evaluation metrics, video-processing pipelines, confidence estimates, visual overlays, and quality-control tools. Derive interpretable behavioral measurements and collaborate with entomologists, laboratory teams, and software engineers to improve imaging standards, annotations, and scientific reliability.

Build and deploy AI agents, intelligent applications, scalable backend services, APIs, and full-stack solutions. Integrate large language models, AI services, data platforms, and external APIs into customer-focused products. Collaborate with engineering, product, and cross-functional teams while contributing to cloud-native applications, data pipelines, distributed systems, testing, deployment, and production operations.

Build and scale AI-powered GTM tools, automations, agents, and workflows for Sales, Marketing, Customer Success, and RevOps. Own automation products from discovery through adoption while measuring efficiency and pipeline impact. Develop and optimize automated outbound programs for North America, testing targeting, messaging, and GTM strategies with sales teams. Translate manual processes into scalable systems and bridge technical and non-technical stakeholders.