Top AI & Machine Learning Jobs

Build and maintain ML infrastructure and data systems for medical imaging: distributed training, RL training stack, high-throughput data pipelines, centralized storage, and production serving to accelerate research-to-production iteration.

Lead AI integration, automation, and software stack rollouts across multi-location clinics. Build AI agents, API-driven workflows, and ad/content automation; manage EMR/CRM integrations; run digital marketing operations and on-site brand activations. Project-manage system deployments and optimize automation to reduce manual work and scale patient acquisition.

Build new features and improve Matilda (app, web, CLI, desktop) in production: ship quickly, improve inference performance, sharpen tooling, own projects end-to-end on the teams cluster in a small, high-agency engineering team.

Build and maintain a provider-agnostic LLM interoperability layer: transform OpenAI/Anthropic spec calls to other provider formats, implement session management, support provider features (skills, batching), and improve developer experience via the Python SDK. Work closely with founders and engage with users to ship production features.

Design, build, and validate cloud data infrastructure and high-throughput pipelines for multimodal sensor (LiDAR, camera, GNSS/IMU) data. Ensure data quality, lineage, versioning, automated validation, IaC, and production stability while partnering with SW/ML teams and labeling vendors.

Design and guide enterprise-scale, cloud-native solutions leveraging software engineering and AI. Provide technical leadership across SDLC, design mobile/cloud apps, integrate via APIs and data services, implement CI/CD and release/configuration practices, and architect end-to-end ML pipelines for cloud and edge deployment while aligning solutions with business objectives.

Build, ship, and operate backend services and AI/agent systems for an AI health coach. Own features end-to-end, contribute to architecture, write well-tested observable code, prioritize privacy/security of health data, and collaborate with product, design, and data teams to deliver production software.

The role involves building and optimizing compression technology, designing neural models, and enhancing training systems for efficient and effective codec production.

Build and deploy production AI agents for customers by identifying high-value workflows, integrating CRMs, documents, data warehouses, and APIs, and debugging agent behavior and data quality. Own the technical customer lifecycle from deployment through adoption and expansion, collaborate with technical stakeholders, and translate customer patterns into product improvements. The role combines software engineering, customer engagement, product thinking, and AI systems implementation.

Develop machine learning classifiers, scalable analytics programs, and automated anomaly detection systems. Process and validate structured and unstructured large datasets, improve data collection, perform ad hoc analysis, and clearly present results. Work across development and data science, using Hadoop, Hive, HDFS, Spark, Elasticsearch, Zeppelin, Python, Java, and data science libraries. Apply statistics, machine learning algorithms, data visualization, and NoSQL technologies.