Top AI & Machine Learning Jobs

Supports applied AI projects from client discovery and strategy through solution development, testing, implementation, monitoring, and documentation. Builds AI-powered workflows, automations, custom GPTs, prompt workflows, data pipelines, and integrations using Python, APIs, low-code tools, and AI services. Collaborates with consultants, engineers, sales, and clients while explaining technical concepts clearly to non-technical audiences. Researches emerging AI technologies and helps deliver reliable, production-ready business solutions.

Build large-scale machine learning systems for advertising, including ranking, recommendation, targeting, prediction, optimization, and creative generation. Develop feedback loops connecting generative AI outputs to advertising performance signals, apply prompt engineering and post-training methods, run experiments, and ship reliable production ML systems. Collaborate across Product, Research, Engineering, and go-to-market teams to deliver AI-native advertising products.

Lead end-to-end design, delivery, and lifecycle management of production AI/ML solutions for strategic clients. Translate business requirements into scalable, secure ML architectures, drive deployments, monitoring, governance, and mentor teams while collaborating with stakeholders across sales, engineering, and data science.

Supports development, integration, simulation, testing, and deployment of Level 4 autonomous commercial vehicle systems. Responsibilities may focus on perception, planning, or control algorithms, including object detection, image segmentation, sensor fusion, trajectory planning, vehicle control, system integration, SIL/HIL validation, on-road testing, root-cause analysis, and closed-loop performance improvement. The intern collaborates with engineering teams and external partners to diagnose field issues and implement system-wide fixes.

Own the full lifecycle of detection and tracking models, including data curation, annotation, training, evaluation, optimization, and deployment to embedded edge platforms. Develop object detection and multi-object tracking systems using mission-specific sensor data, diagnose performance issues, and collaborate with systems engineers to integrate models into the Altra platform. Optimize models for SWaP-constrained environments and support electro-optical and infrared modalities.

Build and operate production AI agent features for Plane, including agent workflows, MCP servers, retrieval systems, customer-facing interfaces, evaluation harnesses, tracing, permissions, and audit models. The role requires shipping reliable LLM-backed features to real users, managing tool calling and failure recovery, measuring quality and performance, and partnering with engineering and product teams to deliver production surfaces.

As an AI Software Engineer, you'll design, develop, and support AI applications, optimizing integrations and ensuring quality solutions aligned with business needs.

Evaluates emerging AI technologies, platforms, infrastructure, and vendors through technical assessments, proof-of-concepts, benchmarks, and pilot deployments. Assesses solutions for capability, cost, risk, scalability, and business value; recommends adoption strategies; supports customers and internal stakeholders; delivers technical presentations, workshops, and demonstrations; and monitors developments in LLMs, automation, and agentic workflows.

Conduct research in representation learning and agentic learning for AI agents that work with diverse data modalities. Develop innovative methods for data representation, sampling, semantic ontologies, and agent optimization. Collaborate closely with engineers to rapidly deploy research into production and improve data science workflows, including data discovery, exploratory analysis, modeling, and data-driven storytelling.

Build and ship AI-powered product features end-to-end across frontend, backend, agents, and evaluation systems. Embed with sales, service, and underwriting operators to identify problems, prototype rapidly, measure impact, and iterate. Own metrics and production outcomes, stay on the cutting edge of models and AI tooling, and present results to the company.