Top Remote Python Jobs in Boston, MA

The Principal ML Engineer will lead the machine learning platform engineering team, providing hands-on technical leadership, mentorship, and code reviews. They will ensure operational excellence by delivering superior infrastructure, collaborating with product managers and data scientists, and guiding innovation in AI/ML technologies.

You will collaborate with business experts to create AI solutions, oversee data management, design and deploy AI systems, and share knowledge with teams. A focus on continuous learning and staying updated on AI advancements is essential.

The Principal Full-stack Software Engineer will architect and build advanced AI interfaces for seamless human-AI interaction, implementing real-time streaming and feedback systems while working closely with ML engineers. The role requires strong frontend architecture and software engineering skills to ensure intuitive user experiences with Hivemind's AI technology.

As a DevOps Engineer on the Cloud Operations Team, you will create and implement automation tools, collaborate with engineering to enhance product quality, maintain 99.9% uptime for customers, and manage infrastructure automation and tooling. You'll also facilitate a smooth onboarding process for new customers while working with international teams.

As a Full Stack Engineer, you will develop and maintain both backend services and frontend components for a data labeling platform. Your responsibilities include designing APIs, creating responsive user interfaces, collaborating with teams on product goals, and mentoring junior engineers.

The Staff Machine Learning Engineer will develop and implement AI/ML models, collaborating with cross-functional teams to drive innovations for Twilio's Efficiency Engineering team. Responsibilities include deploying machine learning models, integrating enterprise data sources, and leveraging advanced technologies, especially for AI solutions that meet diverse customer needs.

The Quantitative Software Engineer will design and implement strategies for managing risk and optimizing DeFi protocols. Responsibilities include developing tools, building data pipelines, refining data models, and collaborating to develop new features, all while staying abreast of industry trends and innovations.