Top AI & Machine Learning Jobs

Own the evaluation, selection, optimization, and production deployment of large language models powering legal and medical document workflows. Build EvalOps and monitoring frameworks, benchmark model quality, cost, speed, and resilience, manage model transitions, optimize RAG and orchestration pipelines, and reduce hallucinations. Partner with product and go-to-market stakeholders while independently implementing changes across staging and production.

Lead Dwellci AI’s technical vision, engineering organization, AI model development, and scalable 3D generative design platform. The CTO will establish architecture and engineering practices, build and mentor an AI team, guide product innovation, collaborate with founders and designers, engage investors, and advance generative AI, computer vision, and computational design capabilities for architecture.

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.

Owns the strategy, architecture, prototyping, and delivery of enterprise AI and automation solutions. Partners with business and technical leaders to identify opportunities, design agentic workflows and integrations, evaluate AI platforms, ensure security and governance alignment, and guide operational rollout. The role also supports product planning, facilitates ideation workshops, advises executives, and co-leads AI enablement and training programs to drive organizational adoption.

Develop and maintain advanced data processing, entity resolution, and data cleansing pipelines using Python and SQL. Responsibilities include NLP, information extraction, data validation, query optimization, testing, deployment, monitoring, code reviews, and maintaining data integrity, privacy, security, and reproducibility. The role requires expertise in record linkage, named entity recognition, text processing, matching strategies, and machine learning libraries, with on-site work at SSA headquarters in Woodlawn, Maryland.

Build and operate secure, scalable AI/ML platform capabilities on AWS. Develop automation, infrastructure-as-code, CI/CD pipelines, AI model deployment and lifecycle services, generative and agentic AI integrations, data connections, governance controls, monitoring, and reliability capabilities. Collaborate with data scientists, engineers, architects, security teams, and stakeholders while evaluating emerging AI technologies and contributing to reusable platform standards.

Designs and operates enterprise AI platforms and cloud deployment architectures for supply chain and digital products. Responsibilities include building AI/ML and GenAI applications, APIs, data products, model-serving systems, RAG and agentic workflows, CI/CD, MLflow lifecycles, observability, governance, and validated GxP releases. The role also establishes engineering standards, integrates SAP data, improves reliability and cost efficiency, and mentors engineers while partnering with product, cybersecurity, quality, validation, and infrastructure teams.

Supports data science solutions for natural gas utility operations through exploratory analysis, feature engineering, statistical and machine learning model development, forecasting, optimization, data validation, visualization, and documentation. The intern will work with operational, weather, telemetry, billing, and usage data; contribute to Microsoft Fabric pipelines; complete an assigned project; and present findings to data teams and leadership.

Build and own AI-powered product features end to end in a Seed-stage startup. Translate product needs into scalable solutions, prototype rapidly, integrate evolving AI models and frameworks, and maintain production quality. Contribute across frontend, backend, and infrastructure while shaping technical direction through hands-on engineering rather than people management. The role requires strong ownership, customer focus, communication, and comfort with ambiguity.

Lead architecture across engineering teams and design AI-augmented capabilities for a regulated payment-integrity platform. Map the current architecture, create AI and platform roadmaps, establish integration and security standards, build reusable software assets, and ship an extensible AI MVP. Define governance, evaluation, and bias-testing methods while advising sales, operations, customers, and executives on practical AI adoption.