Machine Learning Jobs in Cambridge, MA

The Staff Software Engineer will lead the development of cloud-side ML infrastructure, focusing on real-time computer vision and LLM applications, while mentoring team members and improving operational reliability.

The Staff ML Engineer will lead architecture decisions for ML infrastructure, operate real-time computer vision systems, and mentor engineers, ensuring high-quality ML deployment and operational excellence at SimpliSafe.

Lead and deliver AI/ML and computational projects that accelerate pharmaceutical R&D across preclinical-to-clinical stages. Build, scale, benchmark, and maintain agentic systems combining ML and computational biology tools; manage cross-functional teams; drive strategy, resourcing, best practices, and stakeholder communication across ventures and platform partners.

Lead a team building large-scale ML model evaluation and orchestration frameworks for autonomous vehicles. Own data analysis workflows, dataset creation, statistical model evaluation, regression reporting, and tool development (AWS Kubernetes orchestration, ReSimulation). Provide technical leadership, mentorship, and manage project timelines and deliverables.

Lead product strategy and execution for DriveWell Fusion, focusing on telematics data cleansing, signal processing, and AI/ML model development. Collaborate with engineering, customers, and cross-functional teams to integrate map data, deliver actionable driving insights, and use Databricks/Tableau analytics to inform roadmap and adoption. Serve as primary product contact, prioritize features, and drive customer-facing advisory work to improve safety and engagement.

Architect and manage ML pipelines for training and deployment on cloud platforms, automate CI/CD, and ensure system performance and availability.

The Machine Learning Scientist will build and integrate ML models, analyze data, design scalable pipelines, and ensure robust model testing.

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.

Lead a small ML engineering pod to turn research into production: design and operationalize training pipelines and low-latency inference services for computer vision, document intelligence, and predictive models. Drive R&D execution, benchmarking, prototyping, migrations from frontier models to fine-tuned/open-source solutions, and mentor early-career engineers while aligning research with product timelines.

The Machine Learning Architect will deploy models on prototype hardware, adapt algorithms for new environments, and collaborate with hardware engineers to define architecture based on practical insights.

As a Machine Learning Scientist at Nucs AI, you will develop innovative ML methods for medical image analysis, collaborate with clinicians, and contribute to clinical validation studies, impacting cancer diagnostics.

Design and develop auto-labeling algorithms for autonomous driving, collaborating with ML engineers to enhance data quality and efficiency in model training.

Lead multiple AI/ML computational projects across early-stage ventures, define AI strategy, oversee method and pipeline development (including protein design, docking, LLM agents), ensure benchmarking/scaling/productionization, mentor and manage cross-functional teams, scout literature, and represent the organization to partners and conferences.

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.