Artificial Intelligence Jobs in Cambridge, MA

Early-career Data & AI Engineer supporting client work and applied R&D. Prepare, clean, and validate heterogeneous data; build reproducible Python/SQL workflows; support ML and generative-AI tasks (embeddings, RAG, evaluation); prototype tools; document assumptions; participate in code review and translate project lessons into reusable assets.

Lead client-facing, end-to-end AI strategy engagements: scope opportunities, design solutions, build roadmaps, and oversee implementation. Advise C-suite on AI adoption, value realization, governance, and technical enablement. Maintain hands-on fluency with modern AI stack and platforms, drive business development, mentor consulting teams, and contribute to an AI Center of Excellence.

Design, build, scale, and maintain the companys e-commerce marketplace platform using AI-assisted workflows. Deliver production-quality full-stack features, validate AI-generated code, mentor engineers, improve systems, and partner with Product and Design to execute initiatives.

Lead design, training, and deployment of large-scale ML models (LLMs, diffusion, GNNs). Own end-to-end training pipelines, distributed training, evaluation, and inference architecture. Collaborate with data and infra teams, drive reproducible model development, and provide technical leadership and mentorship from research through production.

Architect and lead AI-hardware co-design solutions from research to validated proofs-of-concept. Quantify compute trade-offs with high-fidelity simulation, optimize algorithms for hardware (memory, dataflow, precision), select compute substrates from MCUs to custom accelerators, mentor engineers, and translate innovation into deployable systems while driving thought leadership in Edge AI.

Seeking a Senior AI Engineer to develop AI solutions, oversee project delivery, and collaborate on system architecture. Requires 5+ years with Python and AI technologies.

Own a product area end-to-end: discovery, specification, prototyping, and handoff. Use AI to draft and prototype, keep version-controlled docs in GitHub, triage work and bugs, decompose features into plans, and collaborate directly with engineers and designers to drive shipped SaaS outcomes.

Build and ship agentic AI features across the full stack: design LLM-driven workflows, implement backend APIs and frontend UI, integrate MCP server capabilities, monitor production behavior, and iterate based on customer use. Drive projects independently, collaborate with product/design/engineering, and use agentic coding tools to prototype and deliver end-to-end features.

Forum Ventures seeks a founder to build startups that remove vendor lock-in in edge AI: developing edge runtimes, compiler abstractions, intelligent inference routing, and unified operational planes for mixed NPU fleets. The founder will build product, hire and lead teams, validate markets, and work with Forum’s venture studio for funding, GTM, and operational support to reach early traction.

Lead and build a B2B SaaS startup focused on real-world digital representations of physical assets (utilities, dams, bridges, fiber). Validate product-market fit, sell to utilities/DOTs/infrastructure owners, build capture networks delivering audit-grade field truth, recruit and lead teams, and work with Forum’s funding, GTM, and operating support to reach early ARR and scale.

Seeking a founder to build B2B SaaS startups addressing physical cybersecurity where AI controls critical infrastructure: adversarial robustness, sensor and control-loop integrity, and incident response/forensics. Partner with Forum for funding, go-to-market support, hiring, and product validation to reach early ARR and scale.

Lead a new AI-driven B2B SaaS company focused on physical assets: validate product-market fit, build teams, develop IoT/telemetry-enabled products, drive GTM to early ARR, and collaborate with Forum for fundraising and operational support.

As an AI Product Specialist at Kensho, you will drive market expansion, manage customer engagement, and leverage AI product strategies while collaborating across teams to ensure effective go-to-market execution for AI solutions.

Build and operate production-grade AI agent systems and connectors into governed data (Bronze layer). Design multi-agent workflows, enforce data contracts, implement observability, guardrails, cost controls, governance, and durable documentation while collaborating with stakeholders.

Lead system-level architecture and detailed design of ultra-low-power analog and digital AI accelerators. Translate product requirements into block-level specs, explore novel intelligence representations, develop system models with Synopsys Platform Architect, inform RTL and verification, and collaborate across compute IP, firmware, physical design, and partners while providing technical leadership and mentorship.

The Investment AI Engineer will design, build, and operate AI workflows for investment processes, collaborating with researchers and portfolio managers to improve automation and efficiency.

Founder role to build a B2B SaaS company focused on AI compute economics and GPU/ML infrastructure. Partner with Forum Ventures for funding, GTM, product and hiring support. Validate product-market fit, lead engineering and go-to-market, and raise seed/Series A. Must have domain expertise in GPU/cloud economics or ML platform, attract and lead teams, and operate in North American time zones.

Lead design, development, and scaling of a production-grade, multi-tenant AI agent platform. Own technical roadmap, architecture, reliability, observability, and developer experience. Build and mentor a team of platform engineers, drive multi-agent orchestration, LLM integration, security, and cross-functional delivery for enterprise-scale AI workflows.

Lead North America Commercial AI strategy and deliver production AI/LLM solutions (RAG, agentic workflows, predictive models) for patient finding, HCP engagement, next-best-action, and commercial operations. Partner with Commercial, Data Science, IT, Legal, and Compliance to prioritize use cases, evaluate vendors, productionize models, enforce responsible AI and monitoring, and measure business impact and adoption.

Lead AI, automation, and Microsoft 365-driven digital transformation to streamline workflows, reduce costs, design scalable business systems, and build an AI learning institute. Partner across teams, manage cross-functional projects using Agile, ensure privacy/compliance, and deliver training to increase AI literacy and adoption.

Perform disciplined outbound prospecting and run the full pre-sales cycle from cold outreach to qualification and initial deep dives. Create and advance commercially meaningful AI/SaaS opportunities, engage senior stakeholders and economic buyers, articulate Quantanite's AI-enabled value proposition, and help convert high-value deals while maturing into a full Account Executive within six months.

Design and deliver AI Agent solutions for Veeva Labeling, build prototypes and production features (data flow, orchestration, prompts), integrate models, collaborate with engineering and UX, evaluate AI agents, and present capabilities to stakeholders. Requires stakeholder communication and independent work in a fast-paced environment.

Drive adoption and growth of Agentforce, Data Cloud, and the Salesforce Platform by partnering with customers to align AI and data capabilities to business objectives. Lead consultative discovery, engage business and technical stakeholders, navigate commercial and enterprise buying cycles, and collaborate with internal teams to deliver multi-cloud AI solutions that expand platform adoption and measurable AI-driven outcomes.

Lead technical discovery and demos for enterprise prospects, translate pain points into LLM-powered solutions, present architecture and value, and feed customer insights to Product, Marketing, and R&D to shape the platform and sales strategy.

Own and operate OnRamp's AWS platform and deployment systems, build CI/CD and agent infrastructure, apply LLMs and coding agents to automate DevOps, ensure observability, reliability, security and compliance (SOC 2/HIPAA), and create developer-facing automation to increase team velocity.