Top AI & Machine Learning Jobs

Lead development and productionization of advanced forecasting and predictive models: assess existing analytics, define data needs, design methodologies, run proofs-of-concept, architect cloud-based model deployments, and monitor model performance while translating results for business stakeholders.

Lead architecture and hands-on development of reusable customer-facing AI platform services, including conversational AI, agent orchestration, retrieval, grounding, memory, tool integration, and policy enforcement. Define APIs, data models, deployment designs, testing, evaluation, and operational requirements. Build production systems across GCP and Azure while driving reliability, security, observability, CI/CD, and technical standards. Provide staff-level influence through architecture reviews, mentoring, code reviews, and cross-functional leadership without direct reports.

Develop data-centric machine learning solutions for autonomous driving. Design dataset mixtures, curation and mining methods, model-training recipes, scaling studies, and offline evaluations using real and synthetic driving data. Apply self-supervised learning, imitation learning, reinforcement learning, and foundation-model fine-tuning. Train models across large multi-GPU and multi-node datasets, diagnose data-related failures, and collaborate on deploying models into onboard driving systems.

Develop predictive and prescriptive models, machine-learning algorithms, analytical data pipelines, visualizations, and user interfaces supporting quality-process decisions. Analyze structured and unstructured data, monitor model performance, document solutions, and collaborate with cross-functional technical and business teams to deliver scalable AI and data-science projects.

Develop scalable data science and statistical analytics solutions to monitor emerging vehicle safety hazards. Analyze large structured and unstructured datasets, detect anomalies and trends, support safety investigations and root-cause analysis, automate recurring workflows using Python, SQL/Spark, and Databricks, and communicate findings through visualizations and presentations to technical stakeholders and senior leadership.

Lead design and development of full-stack .NET solutions and AI-powered agentic workflows. Build RAG/LLM systems, microservices on AKS, ETL with Azure Synapse, integrate enterprise APIs, maintain CI/CD, mentor engineers, and support DevOps/SRE practices.

Design, build, and scale AI-enabled workflow and automation solutions across collaboration platforms and enterprise systems. Translate manual processes into secure, reusable, event-driven automations using Python/JavaScript, integrate AI capabilities like Gemini, implement logging and telemetry, and partner with product, security, and business teams to deploy and sustain enterprise transformation solutions.

Design and build large-scale mapping algorithms and geospatial data systems for automated map reconstruction and maintenance. Develop lane, road-network, geometry, topology, and map-conflation systems; process sensor and third-party data through distributed pipelines; apply machine learning and computer vision for feature extraction and change detection; and create automated validation and quality systems. Partner with perception, localization, simulation, and platform teams while mentoring engineers and driving technical problems into production.

Design and implement AI agents, plugins, automations, and enterprise integrations for HR Technology platforms. Lead requirements gathering, technical analysis, solution design, testing, documentation, deployment, security, and data integrity efforts across HR, IT, and business stakeholders. Integrate platforms including ServiceNow, Workday, and other enterprise applications while supporting the HR automation and AI roadmap.

Identifies and formalizes complex problems, then drives the design, development, and deployment of algorithmic solutions using artificial intelligence, machine learning, and data science techniques. The role connects business problems with data scientists and ML methods to produce actionable solutions.