Top Hybrid Jobs

Conduct independent AI research for predictive toxicology and drug safety. Develop novel deep learning architectures, multimodal models, representations, uncertainty methods, and mechanistic reasoning approaches for heterogeneous biological and chemical data. Design rigorous experiments, benchmarks, ablations, and generalization evaluations while collaborating with engineering and scientific teams to translate validated research into scalable modeling systems. Contribute to scientific strategy, publications, collaborations, and regulatory validation.

Lead the design, training, evaluation, and deployment of large-scale machine learning models, including LLMs, diffusion models, and GNNs. Own distributed training pipelines, dataset interfaces, optimization strategies, model evaluation, serving, and lifecycle management. Collaborate with data, infrastructure, and scientific teams while providing technical leadership through architecture reviews, mentorship, and cross-functional decision-making.

Leads cross-functional process improvement initiatives from scope definition through implementation and measurement. Documents current- and future-state processes using BPMN 2.0, facilitates workshops, analyzes process gaps and root causes, develops recommendations and sustainment plans, and measures improvement outcomes. The role requires stakeholder influence, process modeling expertise, change management, and independent project leadership. Travel among Massachusetts, Connecticut, and New Hampshire may be required, along with emergency restoration assignments.

Leads IT strategy, technology roadmaps, application portfolios, delivery teams, vendors, and support services for corporate functions including HR, payroll, communications, sustainability, and regulatory operations. Translates business priorities into technology investments, oversees delivery and operational stability, ensures cybersecurity and compliance, manages budgets and vendors, drives continuous improvement, and develops team members.

Source passive technical talent through LinkedIn Recruiter, GitHub, Boolean searches, and industry databases. Develop personalized outreach campaigns, use AI and data insights to identify target talent pools, and manage candidate pipelines in the ATS. Support recruiting operations, application tracking, and administrative projects. The role focuses particularly on sourcing sales candidates in technical environments and requires strong communication and cold-outreach skills.

Supports inbound and outbound sales development by qualifying, enriching, routing, and engaging leads across email, phone, and LinkedIn. Maintains Salesforce data, meets response-time and activity targets, supports events, builds sequences, tracks conversion metrics, and collaborates with marketing and sales teams. The role requires strong communication, organization, coachability, resilience, attention to detail, and interest in building a technology sales career.

Own GTM analytics across Sales, Marketing, RevOps, Finance, and Customer Support. Build trusted data and reporting systems, define metrics, develop AI-powered self-service tools, identify business risks and opportunities, and translate complex pipeline and revenue analyses into executive-ready recommendations. Partner with data engineering to maintain data integrity and instrumentation while guiding decisions on investment, headcount, and strategy.

Supports leadership by analyzing business processes, systems, technologies, and operational data to identify improvements. Administers and configures business platforms, provides second-level technical support, conducts system audits, develops reports, validates data, and evaluates workflows. The role advises cross-functional teams, leads improvement initiatives, mentors junior staff, and manages operational adjustments while using statistical and trend analysis to support performance decisions.

Architect and deliver complex distributed systems using Azure cloud-native technologies, microservices, APIs, and event-driven patterns. Lead architecture reviews, reliability initiatives, performance optimization, incident response, and root-cause analysis. Drive adoption of AI-assisted development tools while maintaining security and code quality. Collaborate across engineering, DevOps, QA, and product teams, and mentor engineers on technical design, development practices, and AI-enabled workflows.

Owns the technical health, enhancement, and production support of Amazon Connect contact-center capabilities and an intelligent virtual assistant. Designs contact flows, routing, integrations, and conversational experiences; develops serverless AWS integrations; troubleshoots incidents; improves observability, security, release practices, and documentation; and partners with business, operations, product, security, and vendor teams to deliver reliable customer-facing services.

Build and manage scalable, secure, low-latency backend infrastructure for real-time public safety drone operations. Own live telemetry, video distribution, remote-control links, platform infrastructure, APIs, cloud services, and system reliability. Collaborate with hardware and autonomy teams to support streaming and live drone data across formats. Prototype solutions, optimize performance and cost, and maintain cloud architectures, CI/CD pipelines, and DevOps practices.

Own a portfolio of enterprise and scale-up clients from onboarding through renewal, driving retention, expansion, and measurable ROI. Develop and deliver AEO strategies, audits, technical recommendations, roadmaps, and executive presentations across AI search platforms. Monitor account health, lead business reviews, manage stakeholder relationships, identify risks and growth opportunities, support case studies, and translate client insights into internal product and operating frameworks.

The Applied AI Engineer develops, deploys, and maintains generative AI solutions for insurance products, collaborating on cloud engineering and AI initiatives while optimizing model performance and compliance.

Advises investment clients on using alternative data to answer investment questions. Leads discovery, designs data use cases, presents findings, translates requirements into technical briefs, coordinates cross-functional projects, and develops expertise in investor workflows and Similarweb data assets. Partners with Go-to-Market, Product, Research, Development, and client technical teams to identify new metrics, datasets, integrations, and roadmap opportunities.