Top AI & Machine Learning Jobs

Partner with enterprise customers to identify AI use cases, architect and implement custom applications and integrations using WRITER’s platform, APIs, and Knowledge Graph. Translate complex AI concepts into actionable solutions, collaborate with Product and Engineering, improve technical integration processes, and drive customer adoption, time-to-value, and measurable business outcomes.

Develop and deploy large-scale computer vision and machine learning models for Coupang’s search and product experiences. Responsibilities include experimentation, statistical analysis, scalable model development and serving, A/B testing, researching advanced vision techniques, presenting results to leadership, and mentoring engineers. The role requires applying deep learning, transformers, generative modeling, and other state-of-the-art approaches to user-facing products.

Designs, develops, deploys, and supports generative AI applications, APIs, workflows, and reusable components. Evaluates foundation models and deployment approaches, integrates RAG, prompting, tool use, and agentic patterns, and establishes testing, guardrails, documentation, standards, and observability practices. Advises project teams on architecture, security, GPU capacity, costs, performance, privacy, and responsible AI. Collaborates with engineering, infrastructure, security, operations, and business stakeholders to enable scalable enterprise AI adoption.

Build and maintain predictive models, forecasting algorithms, price elasticity frameworks, and revenue management analytics for dynamic pricing and inventory decisions. Develop SQL and Python data pipelines using large-scale enterprise datasets, calibrate revenue management systems, conduct A/B testing and attribution analysis, and create Power BI or Tableau dashboards. Collaborate with revenue managers, IT, data engineers, leadership, and business stakeholders to operationalize models and communicate quantitative insights.

Build geospatial data pipelines and predictive risk models using LiDAR, terrain, GIS, asset, and weather data. Develop physics-backed simulations for grid risks such as conductor sag, vegetation encroachment, wildfire ignition, and extreme-weather failures. Collaborate with utility GIS teams, establish spatial QA/QC standards, translate complex metrics into investment insights, integrate customer systems, and mentor others in data science and product development.

Build and productionize computer vision and machine learning systems that convert video into reliable workplace safety incidents. Responsibilities include designing Flink-based perception pipelines, training and optimizing models with Triton and TensorRT, implementing tracking and probabilistic reasoning, improving latency and cost, building observability and evaluation systems, integrating ML tooling, and partnering with platform, customer success, GTM, and data operations teams on deployments and data quality.

Build the data infrastructure, integrations, automations, and applied-AI tooling powering ProviderTrust’s revenue operations. Partner with Product, Engineering, Commercial, Marketing, and Data teams to create reliable data flows, workflow agents, GTM intelligence, rep copilots, and multi-channel sequences. Own solutions end to end, measure automation ROI, and translate operational challenges into scalable engineered systems.

Lead technical architecture and thought leadership for AI and enterprise workloads on Akamai’s cloud, edge, delivery, and security platforms. Advise customers and stakeholders, identify AI adoption opportunities, design scalable solutions, guide framework and technology selection, and collaborate with engineers, data scientists, Product Management, and R&D. Shape product roadmaps, provide technical guidance, analyze requirements and data, and develop strategic customer relationships.

Build backend systems that translate computer vision and machine learning outputs into interactive product experiences. Responsibilities include designing perception-to-product data contracts, shipping AI-generated geometry to a canvas, balancing accuracy with user experience, closing human correction loops, and bridging AI/ML and product engineering teams. The role requires Python and TypeScript, familiarity with PyTorch and model postprocessing, data contract versioning, and experience deploying computer vision or ML outputs in user-facing products.

Develop and deploy data science solutions for financial crime and fraud prevention. Responsibilities include understanding, cleaning, validating, and preprocessing client data; engineering features; tuning machine-learning models; optimizing runtime performance; communicating findings; collaborating with client stakeholders and internal teams; and improving data science processes, tooling, and best practices.