Top AI & Machine Learning Jobs

As a Senior Machine Learning Engineer, you will lead model validation for AI systems, challenge model soundness, and build validation tools for high-stakes areas such as credit and fraud prevention.

Build and maintain backend services and large-scale data pipelines for recommendation systems, productionize ML models (batch and real-time), develop vector database capabilities, ensure observability and reliability, lead A/B testing and data-driven decisions, participate in on-call and incident response, and mentor engineers while integrating AI into development workflows.

Lead end-to-end AI product discovery, prototype and ship working ML/AI solutions for HR, Marketing, and Commercial teams. Build first prototypes yourself, partner with engineers to productionize, define success metrics, and drive adoption and business impact.

Lead advanced analytics and ML efforts to extract insights from large-scale historical data, design features and data representations for models and LLM/agentic systems, partner with product and engineering to build data pipelines and prototypes, evaluate AI workflows, and drive innovation through experiments and empirical analysis to inform product strategy.

Lead the technical vision and execution of advanced analytics for defense-focused surveillance: develop and validate ML/graph/ABM models, oversee feature engineering, explainable AI, and validation, automate ETL and data pipelines, mentor staff, present to government stakeholders, and transition capabilities into operational environments.

Lead and manage the underwriting and credit risk model validation team, perform hands-on independent validations of complex ML models, assess data integrity and performance, identify and remediate model weaknesses, partner on MRM framework improvements, and coordinate with audit, compliance, and controls to meet regulatory standards.

Design, build, and maintain AI agents, applications, and automations for finance stakeholders. Translate ambiguous business questions into decision-ready answers, shape data models and semantic views (dbt on Snowflake), prototype rapidly with AI coding tools, and partner closely with business users to deliver production-grade solutions.

Lead end-to-end strategy, roadmap, technical execution, and measurement for Answer Engine Optimization (AEO). Own retrieval, indexing, bot access, measurement systems, and productization; drive cross-functional engineering, market intelligence, and executive communications to optimize visibility and commercial outcomes with frontier LLMs and agentic search.

Design, build, and deploy machine learning solutions in distributed systems; collaborate with engineers and subject-matter experts; evaluate and improve models; ensure data security and compliance; communicate insights to stakeholders; mentor junior data scientists.

Perform data cleaning, exploratory analysis, and build/productionize ML and statistical models (including NLP) to generate business value for service and fluids-analysis domains. Collaborate with cross-functional teams, present findings to stakeholders, and work independently on analytics projects within an Agile environment.