Top Tech Jobs & Startup Jobs in Boston, MA

Lead end-to-end data science projects: acquire and prepare messy datasets, develop and evaluate models tied to business outcomes, operationalize models at scale, run experiments, drive ethics/privacy, partner with customers and teams, and coach cross-disciplinary colleagues.

Lead end-to-end segmentation strategy for Microsoft Advertising, translating business priorities into coverage, capacity, and resource-allocation models. Build measurement frameworks, analytical models, and cross-functional alignment to operationalize segmentation into territory design, quota and capacity planning. Advise senior leaders and continuously refine models using data-driven insights to drive growth.

Leads technical pre-sales engagements for Microsoft Power Platform and low-code solutions. Develops customer win strategies, conducts technical discovery, designs solutions, delivers demonstrations and proofs of concept, and secures technical decision-maker endorsement. Builds executive and partner relationships, supports co-sell opportunities, communicates customer feedback to engineering and product teams, drives adoption, and provides technical leadership through workshops, training, mentoring, and community engagement.

Analyze AI training and inference workloads, build performance models and tools, evaluate hardware-software trade-offs, run silicon microbenchmarks, and guide architecture decisions for large-scale cloud AI systems. The role requires correlating models with measurements, diagnosing performance gaps, and communicating recommendations through technical reports and visualizations.

Lead end-to-end data science for customer-embedded, production solutions: acquire and prepare messy datasets, develop and evaluate models tied to business outcomes, run experiments, deploy operational models at scale, coach cross-disciplinary teams, and drive strategy, ethics, and privacy discussions.

Develop machine learning techniques focused on AI safety, alignment, and trustworthiness. Collaborate with product, research, and engineering teams to design, build, deploy, monitor, and iterate responsible AI systems at scale, from experimentation to production for large language models and distributed AI services.

Leads strategic financial services account strategy, executive relationships, complex enterprise sales, and revenue growth. Connects customer priorities with Microsoft AI, cloud, and digital capabilities while coordinating Microsoft specialists, customer success teams, partners, and stakeholders. Identifies strategic opportunities, manages forecasts and risks, influences decision-makers, and drives long-term account expansion and business outcomes.

Design, train, and evaluate Responsible AI components: fine-tune LLMs (including RLHF), build adversarial agent evaluations and safety mitigations, collaborate with engineering to deploy mitigations at scale, monitor operational performance, and troubleshoot end-to-end issues.

Design, build, test, and operate production-grade, secure, and scalable software and services. Partner with customers to translate requirements into technical designs, drive engineering best practices (CI/CD, testing, observability), deliver end-to-end solutions, lead technical workstreams, and apply AI/LLM approaches where appropriate to produce production-ready outcomes.

Embed with strategic customers to lead end-to-end technical programs, applying AI-assisted engineering to accelerate delivery. Coordinate cross-functional teams, make data-driven decisions, manage risks, and cultivate reusable solution patterns and playbooks to scale impact.