Develop and evaluate machine learning and robotics solutions by building simulated environments for testing and data generation. Collaborate with cross-functional teams to integrate models with hardware and translate project requirements into practical, production-ready solutions.
Design and maintain scalable automated testing suites for UI, API, and database layers while integrating them into CI/CD pipelines. Collaborate with DevOps teams to ensure test execution within containerized environments and maintain high standards for data integrity.
You will build and operate scalable ingestion, ELT/ETL, and orchestration pipelines to transform raw data into clean, AI-ready datasets. Additionally, you will implement real-time data ingestion flows and ensure high data quality through rigorous testing and observability.
You will build and maintain Unity-based field applications while managing client-to-cloud data synchronization and backend service integration. Additionally, you will implement automated testing and leverage AI-assisted development tools to ship high-quality features across the full stack.
Develop and maintain embedded C/C++ software for microcontrollers, including firmware, drivers, and board support packages. Design, simulate, and verify control logic using MATLAB and Simulink while integrating it into heavy machinery applications.
You will own the end-to-end development life cycle of AI agents, from initial scope and design to production deployment and iteration. Additionally, you will act as a strategic advisor to enterprise leaders, helping them define and execute their AI strategy while troubleshooting technical issues.
Design and deliver production-grade AI agents while managing the full Agent Development Life Cycle from pilot to deployment. Partner with large enterprises and startups to solve complex business challenges and guide the evolution of the core platform.
You will take end-to-end ownership of machine learning models, ensuring their reliable deployment and performance on physical hardware. Additionally, you will design and optimize real-time AI pipelines while collaborating with cross-functional teams and clients.
The AI Business Manager will bridge the gap between business and engineering teams to design AI solutions and manage the full project lifecycle from discovery to kickoff. Responsibilities include building commercial proposals, coordinating with technical teams, and maintaining CRM accuracy.
Partner with customers to translate complex business challenges into scalable, production-ready AI solutions. Design and architect end-to-end AI systems while collaborating with cross-functional teams to deliver measurable business impact.
