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

Lead modeling efforts and oversee junior staff for moderate-to-high complexity projects. Develop and update predictive models (GLMs, ML, GenAI), explore deployment solutions, perform ad hoc analyses, coordinate cross-functional delivery, testing, training and support, and resolve problems to ensure timely service to internal and external customers.

Lead development and deployment of ML solutions for claims, including feature engineering, training/validation, MLOps, and LLM/vision models. Mentor junior scientists, run experiments, communicate results, and collaborate cross-functionally to deliver business value.

Lead and oversee modeling efforts across submission, underwriting, and claims. Maintain and update GLM/ML/GenAI models, explore deployment solutions, perform ad hoc analyses, coordinate cross-functional delivery, provide training, and resolve issues to support internal and external customers.

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.

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.

Build and productionize agentic workflows and RAG pipelines, integrate LLMs into the GTM stack, and develop high-performance backend services and ML pipelines. Connect quoting engine, Salesforce, and data lakes, solve synchronization and architectural challenges, and ensure observability, scalability, and reliability for sales automation tools.

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.

Lead design and delivery of low-latency market-making and automated trading strategies. Translate quantitative research into production systems, build backtesting and real-time decision engines, ensure scalability and observability, manage risk-aware optimization, and influence cross-functional teams on strategy and technical direction.

Lead AML model development, optimization, validation, and governance for transaction and customer screening across banking, brokerage, and lending. Build ML/statistical models, maintain vendor solutions, ensure regulatory compliance, document methodologies, produce AML dashboards, and support audits, risk assessments, and stakeholder communications.

Build and operate Coinbase's LLM and agent platform: unified model gateway, AI Hub, secure microVM agent runtime, knowledge base integrations, AI FinOps, observability and evaluation tooling, and production-grade agent deployments with teams across the company.

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

Lead the development of fraud prediction models using machine learning, collaborating across teams to build, scale, and monitor models in production.