Remote Software engineering Jobs

• Design, train, and operate ML systems that power the Tebra platform.
• Own the entire lifecycle from data exploration and model development to deployment.
• Push the boundaries of applied ML in healthcare, transforming messy real-world data into reliable automation.

Build and maintain custom applications, triggers, classes, and components using Apex, Flows, Visualforce, and Lightning Web Components. Design and develop interactive dashboards and visualizations using Salesforce CRM Analytics (Tableau CRM). Work closely with stakeholders to gather functional requirements and translate them into technical specifications.

• Design, develop, and maintain end-to-end features for Cresta’s no-code processing platform.
• Build intuitive UI components and visual editors for configuring conversation logic and workflows.
• Architect and implement backend services and APIs to power a dynamic no-code interface.

• Build and maintain custom applications, triggers, classes, and components using Apex, Flows, Visualforce, and Lightning Web Components in Sales Cloud.
• Design and build responsive email templates using Email Studio and Content Builder in Marketing Cloud.
• Configure automated workflows and customer journeys in Journey Builder.

• Own end-to-end implementation of AI-powered product features, from prototypes to production.
• Mentor other engineers on the team, leveling up the team as a whole.
• Collaborate across the organization to support shipping these features to production.

Design, develop, and maintain scalable services that support the diverse activities of a high-throughput laboratory. Develop both front-end and back-end applications Implement and manage CI/CD pipelines using GitLab. Collaborate closely with end-users and product managers to iterate on requirements and deliverables. Optimize architecture and infrastructure on the AWS cloud platform for performance, scalability, reliability, and cost-effectiveness.

• Lead technical efforts across multiple teams, owning system reliability.
• Mentor engineers and drive improvements that scale beyond a single team.
• Design, develop, and maintain scalable and secure APIs and integration services.

• Lead a cross-functional team of ML engineers, data scientists, and MLOps professionals.
• Oversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment.
• Provide technical direction on large-scale model training, fine-tuning, and distributed systems design.

• Build the backbone of Underdog’s data ecosystem to power seamless communication across our services.
• Create robust, scalable microservices to serve real-time, high-volume data needs for our internal teams.
• Drive impactful technical initiatives from start to finish in a fast-moving, high-stakes environment.

Partner with the data science team to put analyses and visualizations into live production systems. Collaborate with the AWS infrastructure team to build robust tooling and workflows. Develop performant and scalable solutions that put statistical concepts into the hands of users.