Artificial Intelligence Jobs in Cambridge, MA

Lead SimpliSafe's AI organization to define and execute company-wide AI strategy, own AI product roadmap, build cloud and on-device ML/CV platform, manage budget and hiring, partner with Product and Engineering, and translate cutting-edge research into consumer AI features for constrained devices like cameras.

The Principal AI/ML Engineer will lead the design, implementation, and deployment of AI systems, mentor junior engineers, and ensure model performance and reliability in production environments.

Build and maintain production-grade React+TypeScript web interfaces for data-intensive, real-time AI products. Own end-to-end frontend features, optimize UI performance for large datasets, collaborate with design and backend teams, establish frontend best practices, improve architecture and tooling, and resolve production issues across browsers and devices.

Owner/implementer of end-to-end full stack features for data-intensive AI products: design and build scalable Node.js backends, REST APIs, and React+TypeScript frontends; optimize performance; establish testing, observability, and CI/CD; collaborate with product, design, and ML teams; debug and support production systems.

Design, develop, train, validate, and deploy AI/ML products for life-sciences customers. Advise leadership on technical and commercial feasibility, collaborate with cross-functional and commercial teams, and lead projects in RL, LLM agent harnesses, fine-tuning, governance, and model evaluation.

Lead and build an Applied AI organization that turns PSI's AI and physics research into customer-facing solutions. Hire and manage teams, scope and deliver engagements, integrate research and engineering, stay hands-on technically, and partner with sales to drive revenue while ensuring reusable, trustworthy deliverables.

Lead Core AI to build models, agents, and training systems that enable AI-driven physics discovery. Set roadmap, own research portfolio and infrastructure, hire and coach top talent, stay technical as a player-coach, and ensure results are scientifically trustworthy and production-ready for Applied AI and Engineering teams.

Lead design and delivery of an enterprise Agentic AI Platform enabling build/bring-your-own-agents. Architect production-grade services for model integration, orchestration, lifecycle management, observability, evaluation, and performance optimization while partnering with cross-functional teams, enforcing governance and responsible AI, and mentoring engineers to translate experiments into scalable, secure production systems.

Design, build, and maintain secure, scalable integrations between an agentic AI platform and enterprise systems using MCP/A2A, APIs, webhooks, and event-driven patterns. Create reusable connectors and middleware, implement authentication/authorization and secrets management, enable data exchange for structured and unstructured sources, and ensure observability, resiliency, and compliance while partnering across product, security, and platform teams.

Own Halo end-to-end: define roadmap, shape the AI-native consumer experience, coordinate advisor handoffs, and work with engineering and data science to ship multi-agent, compliance-grade AI features. Measure success across a coupled consumer-advisor product, prioritize ruthlessly with limited resources, and embed SEC-compliant traceability into product decisions.

Design, build, and operate AWS-native AI/ML systems: RAG pipelines, fine-tuned LLMs, and microservices. Implement IaC (Terraform), CI/CD, policy guardrails, and production deployments integrating Bedrock/SageMaker, LangChain, and telemetry for secure, scalable enterprise use.

As an AI Engineer, you will develop AI security capabilities, integrate features for vulnerability detection, and maintain APIs for secure interactions while collaborating across teams.

As a Staff Software Engineer in Applied AI, you will architect AI systems for vulnerability detection, collaborate across teams, and improve AI model performance.

As a Senior Software Engineer on the AI Platform team, you will develop AI security features, enhance vulnerability detection, integrate AI patterns, and collaborate across functions to deliver solutions.

As a Senior Software Engineer for Applied AI, you'll develop AI security capabilities, integrate AI models, and improve security workflows within HackerOne's platform while collaborating across teams.

As a Machine Learning Engineer, you will optimize backend services, integrate ML models, collaborate with cross-functional teams, and support continuous improvement initiatives.

The Staff Research Scientist will develop AI algorithms, software simulations, and lead hardware prototyping in a collaborative research team setting.

Build and ship full-stack features for a production AI/LLM platform: implement polished React UIs from specs, own database and access-control/security, integrate multi-provider LLMs (RAG, agentic workflows), and formalize QA by extending test suites with integration and end-to-end coverage.

Quota-carrying sales role generating, qualifying, and closing AI opportunities across an assigned region. Partner with field teams and AI ecosystem partners to build pipeline, craft executive pitch decks, sell product/infrastructure and consulting services, and maintain CRM, forecasting, and GTM operational discipline.

Drive consulting pre-sales for regional AI PODs by scoping, packaging, and positioning AI services (data readiness, governance, AI Factory, workforce AI, coding assistant pilots). Collaborate with sales, architects, and delivery to develop proposals, ensure clean handoffs, justify infrastructure, design lab/PoC engagements, and build repeatable service frameworks to accelerate customer adoption and downstream consumption.

Technical pre-sales AI architect responsible for designing end-to-end enterprise AI architectures, whiteboarding GPU cluster and MLOps solutions, coordinating ATC proof-of-concepts, aligning with NVIDIA and hyperscaler partners, producing BOMs/sizing/POC plans, and enabling clean handoffs to delivery teams while supporting revenue-generation and co-selling activities.

Sell coding-assistant and AI-native engineering solutions and co-sell NVIDIA-accelerated application services. Engage enterprise development leadership to design pilots, benchmark developer productivity, scope consulting engagements, and translate developer tools into business outcomes while collaborating within regional PODs and with NVIDIA technical teams.

Sell, scope, and package enterprise AI consulting services across workforce AI, AI Foundations, and AI Factory use cases. Develop proposals, run discovery workshops and assessments, justify infrastructure investments, design lab/PoC engagements, and ensure clean handoffs to delivery while collaborating with sales, architecture, and delivery teams to grow services pipeline and consumption.

Quota-carrying sales role generating, qualifying, and closing enterprise AI opportunities across an assigned region. Partner with field teams and AI ecosystem partners, craft executive pitch decks, drive product/infrastructure and consulting services sales, manage CRM and forecasting, and deliver multi-phase AI engagements.

Technical pre-sales AI architect responsible for designing end-to-end AI/ML architectures, leading discovery and POC lab engagements, co-selling with sales and partners, producing reference architectures, BOMs, sizing models, and ensuring clean handoff to delivery teams. Operates in a revenue-generating, customer-facing pre-sales role and collaborates with NVIDIA, hyperscalers, and infrastructure partners.