Top Remote Senior Level Machine Learning Engineer Jobs in Boston, MA

Lead and direct multidisciplinary teams to research, develop, test, integrate, and demonstrate advanced signal processing, optimization, and machine learning algorithms for radar, electronic warfare, and sensor systems. Oversee modeling/simulation, algorithm T&E, customer engagement, and technical briefings for defense and intelligence applications.

Lead architecture and technical vision for integrations that ingest external data (e.g., Salesforce, HubSpot) into Jasper's IQ layer. Design scalable, secure data ingestion, define context primitives, drive cross-team alignment, and deliver staff-level initiatives that improve reliability and AI-driven product quality.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

Design and build scalable, automated evaluation pipelines and infrastructure to validate speech, audio, and multimodal models. Translate research benchmarks into enforceable pass/fail gates, run batch and streaming tests, operate canaries and continuous monitoring, integrate quality gates into CI/CD, and partner with research, training, inference, and infra teams to prevent regressions and ensure production model quality.

Build, deploy, and maintain AI-powered agents, APIs, and applications for People operations on Snowflake. Turn messy business requirements into production systems, integrate with Workday/Notion/case tools, ensure data governance and security, design multi-model LLM reliability controls, and operate full lifecycle including CI/CD, monitoring, and incident fixes while partnering with non-technical stakeholders.

Design and deploy machine learning models for financial document processing, optimize large language models, collaborate with cross-functional teams, and guide junior peers in a fast-paced environment.

Design, develop, and deploy machine learning models and pipelines to optimize operations. Lead full ML project lifecycle, ensure model evaluation/monitoring, collaborate cross-functionally, mentor junior engineers, and drive continuous improvement in ML applications and processes.

Lead end-to-end ML systems for identity verification, including document authenticity, face match, liveness and deepfake detection. Build GNN-based identity graphs, behavioral/device-intelligence models, vendor benchmarking/evaluation, and production enforcement. Mentor engineers and align ML architecture with Product, Compliance, Risk, and Security stakeholders.