Top AI & Machine Learning Jobs

Run Agent Operations for Luna, an AI assistant embedded in Microsoft Dynamics 365 Business Central. Monitor agent quality, telemetry, escalations, adoption, and task completion; maintain knowledge and training; support customer configuration and enablement; and translate findings into product, documentation, and workflow improvements. Partner across Customer Success, Product, Development, and Implementation while supporting APIs, integrations, agent interoperability, and AI-assisted customer success operations.

Productionize machine learning systems for large-scale robotic fleets, including deployment infrastructure, predictive robot health monitoring, data pipelines, model validation, telemetry analysis, and fleet-wide rollouts. Collaborate with researchers and cross-functional engineering teams to deploy computer vision and ML models using cloud, edge, and GPU-accelerated platforms. Build simulation environments, dashboards, observability solutions, and scalable CI/CD processes while contributing hands-on Python development.

Own data science for customer-facing product features, including LTV prediction, experimentation, benchmarking, and forecasting. Proactively analyze data to identify customer problems and product opportunities, build and deploy production-grade models, and influence product roadmaps. Partner with Product, Engineering, and Analytics, communicate findings to varied audiences, iterate on shipped features, and lead new data-driven initiatives.

Develop and evaluate AI use cases, prototype solutions, and convert successful proofs of concept into production systems. Partner with engineering, technology leadership, and business teams on AI architecture, platform standards, vendor evaluations, technical guardrails, observability, testing, security, cost management, and workflow adoption. The role also supports cloud deployment, data and backend architecture, and enterprise AI integration.

The Senior Data Scientist applies statistical analysis, machine learning, and advanced analytics to traffic and revenue forecasting, customer behavior, travel patterns, and business performance. Responsibilities include integrating internal and external data, developing and validating models, identifying demand drivers, supporting business development, and communicating insights through visualizations and presentations. The role serves teams across North America and Europe and requires independent problem framing, rigorous analytical judgment, and clear communication with management.

Conduct independent AI research spanning large language models, reasoning, knowledge acquisition, factuality evaluation, and trustworthy AI. Translate research ideas into scalable prototypes, implement and extend state-of-the-art methods, design experiments, develop algorithms and evaluation methods, use AI-assisted development tools, and communicate findings through technical reports and research papers.

Lead research into novel AI architectures, learning algorithms, reasoning, knowledge representation, and evaluation methodologies. Define and execute ambitious research programs, design experiments, develop large-scale content evaluation systems, mentor research engineers, and communicate findings through technical publications. The role combines scientific leadership with hands-on innovation focused on language models, factuality, evidence quality, source reliability, and trustworthy AI systems.

Leads a team of forward-deployed AI engineers delivering production solutions for business functions. Owns AI use-case prioritization, technical quality, governance reviews, champion-network enablement, stakeholder partnerships, and team development. Directs solutions from design through deployment, ensures testing and security standards, coordinates Legal, Privacy, Information Security, and Procurement reviews, and promotes AI adoption through training and ongoing support.

Early-career Scientific AI Engineer in CAS’s rotational TechTAP program. The role applies data science, statistical analysis, machine learning, and AI techniques to scientific and business challenges. Responsibilities include preparing and interpreting structured and unstructured data, designing experiments and prototypes, developing dashboards and data products, evaluating emerging technologies, and communicating recommendations to technical and non-technical stakeholders. Participants also collaborate cross-functionally, support product innovation, and engage in leadership development and mentoring.

Conduct fundamental research in machine learning, statistical methods, foundation models, uncertainty quantification, safety, and trustworthy AI for national security and scientific applications. Develop and apply advanced models, analyze data, conduct experiments and simulations, publish findings, contribute to proposals, and collaborate with interdisciplinary researchers, academic partners, and industry.

Conduct fundamental research on explainable and interpretable machine learning, focusing on learned representations, sparse activation decompositions, concept discovery, mechanistic analysis, causal interventions, and human-in-the-loop workflows. Develop and evaluate deep learning methods, analyze scientific and national security applications, collaborate with domain experts, publish results, contribute to proposals, and document research in technical reports and peer-reviewed publications.

Build custom data ingestion pipelines, predictive models, and production scoring systems for complex enterprise customers. Assess data readiness, resolve messy multi-source data, support identity resolution, and deliver propensity, lookalike, LTV, and lead-scoring models. Collaborate directly with customer data teams and internal account teams, then turn successful custom solutions into reusable platform patterns.

Designs, deploys, and integrates generative AI solutions for clients, including LLM agents, RAG pipelines, workflow automation, and conversational interfaces. Translates business needs into production systems, supports adoption through training and iteration, contributes to AI research and offerings, and assists with business development and publications.