Artificial Intelligence Jobs in Cambridge, MA

The AI Solution Architect will design, implement, and optimize AI systems within the Bluefield framework, mentor engineers, and ensure architectural quality.

The VP of AI & Platforms will lead engineering and data science efforts, focusing on building platforms for seamless ecommerce logistics, accelerating time to value, and scaling teams effectively.

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.

Administer and optimize the Greenhouse ATS, build recruiting dashboards and reports, integrate recruiting tech with HRIS/Slack, design and deploy generative-AI workflows to automate hiring tasks, train recruiters on AI tools and interview plans, and support interview coordination using AI scheduling assistants to improve hiring efficiency and data integrity.

Build and operate production agentic AI systems that convert longitudinal health data into actionable recommendations. Responsibilities include architecting stateful agent workflows, integrating LLMs and multimodal models, implementing retrieval and memory layers, ensuring production readiness and observability, standing up eval pipelines, optimizing cost/latency, and mentoring engineers while partnering with clinicians and cross-functional teams.

Designs, implements, and deploys cloud-native AI/ML solutions and data pipelines to support personalization and optimization. Builds and serves ML models (real-time and batch), develops APIs and front-end tools, automates workflows, and ensures secure, scalable AWS infrastructure. Leads architecture discussions, mentors engineers, manages project lifecycle, and advises senior management on technical strategy and risk.

The role involves developing and integrating ML/AI solutions in agricultural biotechnology, mentoring teams, and promoting data-driven practices.

The Account Executive will manage the full sales cycle for enterprise and scale-up accounts, building relationships with technical buyers and collaborating closely with senior leadership to drive revenue and shape sales strategies.

The Data Analyst will focus on digital consumer/patient experiences, driving measurement and insights, audience activation, and reporting using data analytics and AI solutions.

The Principal Scientist will lead AI-driven research in neurology, focusing on neurodegenerative diseases through data analysis, integration, and AI/ML methods to discover biomarkers and targets.

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

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

Lead AI Engineer responsible for guiding AI engineering teams, overseeing solution design, ensuring code quality, and mentoring AI engineers.

Lead the strategy and development of Epiq's AI-powered product portfolio for legal and compliance solutions, focusing on AI productization, commercialization, and cross-functional leadership to drive growth and adoption.

Design and develop web applications for ML dataset generation and data search. Mentor junior engineers and collaborate with cross-functional teams.

Lead development of a new AI Data Mesh product strategy, collaborating with engineering teams, defining architecture, and ensuring compliance with financial standards while mentoring other product managers.

Lead the product strategy for Scribd's internal developer and agentic platforms: unify AI workstreams, own internal app/plugin/agent runtimes, translate functional needs into platform requirements, drive cross-functional adoption and metrics, and run internal rollouts and evaluation to prove impact.

Lead AI engineering on the Data Platform: build Databricks Apps deployment paths, construct an AI layer over the Medallion Architecture and semantic layer, enable LLM/NLP systems and agentic workflows, embed AI tooling in the developer lifecycle, enforce guardrails for production safety, define metadata/modeling patterns, and mentor engineers to accelerate AI adoption.

Lead the creation and scaling of an AI-native accounting agent startup: refine strategy and pricing, run customer pilots with CPA firms, partner with product/engineering to ship V1, lead fundraising, and recruit and build the founding team and company culture.

Audit and ensure quality of data labeling work for ML using human-in-the-loop processes. Provide feedback, train and support annotators, monitor workflows, identify recurring issues, and help improve guidelines and processes.

Evaluate AI model outputs, perform audit-style reviews to find patterns and failure modes, apply and refine labeling/evaluation guidelines, document findings, communicate insights to leads and stakeholders, and participate in team calibrations to improve model evaluation and data quality.

Evaluate AI outputs, perform audit-based reviews, identify patterns and failure modes, apply and improve annotation/evaluation guidelines, document findings, and communicate insights to cross-functional teams to improve model performance and evaluation frameworks.

Evaluate AI model outputs, perform audit-based reviews to identify patterns and failure modes, apply and refine guidelines, document findings, and collaborate with leads and cross-functional teams to improve model evaluation and data quality.

Support AI/GenAI risk assessments, evaluate cloud and IT controls, contribute to model governance and documentation, and translate technical design into risk and control implications. Collaborate with engineering, data science, cybersecurity, and audit teams to produce client deliverables and strengthen AI, data, and cloud compliance programs.