Top Tech Jobs & Startup Jobs in Boston, MA

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Design realistic, specialty-specific clinical case scenarios and gold-standard attending-level responses, evaluate and grade AI-generated outputs using structured rubrics, provide detailed written feedback to improve model clinical reasoning, and participate in onboarding, calibration, and review sessions in a fully remote, asynchronous contractor role (~20 hours/week).

Build, manage, and scale cloud infrastructure using Terraform/IaC on AWS; automate deployment pipelines; maintain system reliability and security for a real-time data detection platform.

Analyze and classify technical content for security vulnerabilities, apply pattern recognition to improve AI model threat detection, design and evaluate security problems, and collaborate asynchronously with domain experts to produce high-quality outputs.

Manage and optimize end-to-end account reconciliations, intercompany eliminations, and chart-of-accounts governance. Identify discrepancies, perform variance analysis, and implement AI-driven automation and anomaly detection to reduce manual effort and accelerate close. Collaborate with cross-functional teams to resolve mismatches and improve financial data quality and reporting accuracy.

Senior sales hunter responsible for acquiring new enterprise clients for Analytics, AI/ML, GenAI, Data Science, and Data Engineering consulting services. Build CXO relationships, manage full sales cycle from prospecting to close, hit revenue quotas, leverage strategic partnerships (Microsoft, Databricks), and travel nationally to engage clients.

Develop and maintain checkers for competitive programming problems allowing multiple valid outputs, verify participant submissions, write clear C++ code, document logic, collaborate with customers, and provide feedback to improve test cases and checkers.

Build and maintain operating and cash-flow models, apply AI/ML and data techniques to automate forecasts, run sensitivity and scenario analysis, translate strategy into financial outcomes, support fundraising/M&A/pricing, and create dashboards and reports for stakeholders.

Act as the internal voice of the customer, partnering with Sales, Product, and Engineering to design and configure billing, revenue recognition, and invoicing solutions. Lead discovery with finance leaders, build demo/sandbox environments, respond to RFPs, document handoffs, and create onboarding materials while advocating customer needs to Product and Engineering.

Provide mechanical engineering domain expertise to create and review technical content used to train AI systems: review documents, develop and assess questions/solutions, give written and oral feedback, collaborate cross-functionally, resolve complex engineering problems, and improve data quality while working independently.