Top AI Jobs in Boston, MA

The Applied AI & Analytics Associate will conduct high-impact analytical work across functions, utilizing AI and data to drive business decisions and improvements, while collaborating with senior stakeholders and building analytical tools and models.

Lead architecture, design, and delivery of Klaviyo's Customer Agent conversational AI platform. Drive technical strategy, build scalable AI-enabled features, establish observability and reliability practices, mentor engineers, and coordinate cross-functional initiatives to deliver production agentic systems for millions of users.

Lead architecture, design, and implementation of a scalable conversational AI platform (Customer Agent). Drive technical strategy for LLM-powered agentic systems, retrieval, orchestration, memory, evaluation, and reliability. Ship AI product features, establish observability/testing/operational best practices, lead cross-functional initiatives, mentor engineers, and evaluate emerging AI technologies to deliver reliable customer-facing experiences.

Build and maintain internal agentic AI platforms and developer-facing tools that integrate LLMs with engineering workflows. Partner with product and infra teams to design standards for agent deployment, reliability, evals, security, onboarding, and adoption measurement to improve developer productivity.

As an Applied Researcher II, you will create AI systems for banking, working with cross-functional teams to develop and implement AI-powered products, while conducting applied research and engaging with emerging technologies.

The role involves partnering with a team to deliver AI products, utilizing various technologies and conducting applied research to enhance customer experiences leveraging AI.

This role involves leading the development of AI-powered products, optimizing large scale AI systems, and mentoring cross-functional teams. It focuses on designing and deploying AI components, contributing to the technical vision, and applying cutting-edge AI techniques.

Lead design, build, deploy, and support of foundational AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Optimize production LLM performance (cost, latency, throughput) and contribute to long-term technical vision.

Lead development and deployment of foundational AI systems: design, build, test, and support LLM training and inference, similarity search, guardrails, observability, and optimizations for scalability, cost, latency, and throughput while shaping technical vision and collaborating with cross-functional partners.

Lead design, development, deployment, and support of foundational AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, and observability. Optimize large-scale AI performance (cost, latency, throughput), partner cross-functionally, and contribute to technical vision and roadmap.

As an Applied Researcher I, you will partner with a cross-functional team to develop AI-powered products, build AI foundation models, and conduct high-impact applied research in machine learning.

As an Applied Researcher I, you'll partner with cross-functional teams to deliver AI-powered products, build foundation models, and engage in applied research on advanced AI techniques.

The Senior Lead AI Engineer will develop and support AI software components, collaborate with cross-functional teams, and enhance banking experiences through AI systems.

Conduct applied research and build AI foundation models, particularly large language models and agentic AI systems, across design, training, evaluation, validation, and production implementation. Partner with data scientists, engineers, and product managers to deliver scalable AI products. Research optimization, fine-tuning, robustness, explainability, and related deep learning methods while translating technical findings into business outcomes and independently pursuing impactful research agendas.

The Lead AI Engineer will design, develop, and support AI software components, leveraging various AI technologies to enhance banking services. The role involves partnering with cross-functional teams to deliver AI-powered products and optimize large-scale production AI systems.

Design, develop, test, deploy, and support production AI systems, including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, experimentation, and observability. Develop state-of-the-art optimization techniques to improve scalability, cost, latency, throughput, and hardware utilization. Shape the long-term technical roadmap for foundational AI platforms while collaborating with engineers, research scientists, program managers, and product managers. Lead and mentor engineering teams and influence senior cross-functional stakeholders.

Design, build, deploy, and support large-scale AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, and observability. Collaborate cross-functionally, optimize model performance and cost, and contribute to technical vision and roadmap for foundational AI platforms.

The role involves developing AI-powered products, conducting applied research, collaborating with a cross-functional team, and building AI foundation models. Candidates should be innovative, technical, and have a deep understanding of AI methodologies.

Architect complex embedded hardware and software systems for next-generation audio products. Evaluate feasibility, tradeoffs, scalability, and system constraints across power, compute, memory, latency, performance, and security. Develop simulations, prototypes, AI agents, and automated engineering workflows for architecture exploration and verification. Translate audio, sensing, machine learning, and AI technologies into reusable platforms, frameworks, algorithms, and IP while providing principal-level technical leadership across engineering teams, suppliers, and partners.

Develop, optimize, and deploy audio and multimodal machine learning models on embedded and edge devices. Build real-time inference pipelines, convert models to efficient C/C++ implementations, and optimize latency, memory, SRAM, and power across MCUs, DSPs, NPUs, and accelerators. Collaborate with researchers, DSP experts, firmware engineers, and hardware teams to deliver production-ready embedded AI systems using model development, quantization, profiling, and on-device runtimes.

Own strategy and execution for Klaviyo's Analytics AI product area, principally the Analytics Agent. Define quality measurement, AI-generated analytics UX, and query infrastructure transitions. Partner cross-functionally to ship data-grounded LLM experiences, ensure metric accuracy and platform health, write rigorous product specs, and support multi-brand Enterprise analytics needs.

The Applied Researcher II will work on developing AI foundation models, partner with cross-functional teams, and engage in impactful research to enhance customer experiences using advanced AI techniques.

Design, develop, deploy, and support foundational AI systems, including model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale production AI systems for scalability, latency, throughput, cost, and hardware utilization. Partner with engineers, scientists, technical program managers, and product managers while contributing to technical vision, roadmap development, and responsible AI practices. Lead and mentor engineering teams and apply emerging AI research to production systems.

Lead design and implementation of enterprise AI architectures and integration solutions, manage multiple projects and executive client relationships, drive strategic technology planning and business development, mentor teams, conduct market research and feasibility studies, and promote technological innovation across the firm.

Lead Microsoft Dynamics 365 CRM implementations, architect solutions, manage project lifecycles and client accounts, mentor teams, ensure quality and post-go-live support, and drive innovation and continuous improvement.