Top AI & Machine Learning Jobs

Senior individual contributor combining clinical informatics and hands-on Databricks engineering to build and deploy AI/ML and rules-based algorithms that detect documentation/coding gaps and clinical process variation. Translate ranking methodology into data requirements, build scalable Databricks pipelines and models, partner with CDI/coding/quality, and advise executive leadership to drive performance improvement and public ranking outcomes.

Lead cloud modernization as a Senior Azure Architect: assess AWS/Azure workloads, design Azure-native solutions, own Azure data platform and analytics, define AI architecture and model strategy, and migrate Citrix to Azure Virtual Desktop while enforcing security, governance, and cost optimization.

Build and ship end-to-end AI-enabled tools, agents, copilots, and automations embedded in clinical and operational workflows. Own architecture, data integrations, prompts, evaluation, monitoring, and adoption. Embed with frontline teams to redesign workflows, measure impact, and iterate while ensuring privacy, security, and regulatory compliance.

Work with the blockchain security team to design, fine-tune, and integrate LLM-based AI agents that automatically analyze smart contracts, improve threat detection and risk assessment, and translate research into scalable security auditing tools.

Build reference implementations, demos, and tooling for You.coms AI search and retrieval APIs; contribute and maintain open-source projects; engage and support the developer community; reduce inference cost and improve model performance; represent the company at events and translate technical work to business stakeholders.

Lead enterprise data science and competitive intelligence efforts, building AI-driven market intelligence, RAG/LLM solutions, executive dashboards, portfolio analytics, and strategic recommendations to inform leadership, risk, and regulatory needs across consumer lending, payments, and fintech.

Lead and deliver high-impact ML solutions for telecommunications: set vision and roadmaps, implement and oversee research-grade models, mentor data scientists, align cross-functional teams, improve data foundations, and scale robust MLOps-driven products.

Design, develop, deploy, and maintain AI/ML models and automation across ministry systems. Build data pipelines, LLMs, RAG, and integrations with cloud AI services. Ensure model performance, security, data governance, and ethical AI practices while training teams and supporting cross-functional initiatives.

Build and productionize ML systems for personalization, search, and recommendations. Apply statistical and ML models using Python and SQL, collaborate with stakeholders, and measure business impact across cloud environments.

Partner with clients to define data science strategies, conduct analyses, create roadmaps and business cases, communicate methods to non-technical audiences, collaborate on end-to-end solutions, and identify/deploy ML and GenAI solutions.