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Embedded Firmware Engineer
Karman, an NVIDIA-backed company applying AI to electric-grid power orchestration for AI data centers, seeks an early-career Embedded Firmware Engineer (0–3 years) to write production C/C++ firmware for resource-constrained microcontrollers across multiple hardware variants, plus build CI/CD, HIL test infrastructure, and diagnostics tooling. Remote anywhere in the US; Michigan preferred.
Generative AI Application Engineer
Mid-level, hands-on engineer for a SaaS data analytics company serving banks, building production generative AI features (LLM-API applications, agents, evaluation/monitoring harnesses) in Python and SQL, deployed on Azure. Remote US role on Eastern hours; candidates must have verifiable shipped GenAI apps and reachable references.
Data Scientist - Remote
Data scientist building machine learning and statistical models on cloud services to modernize AI in healthcare — collecting and cleaning large clinical datasets, developing predictive models, and communicating insights to clinicians and business stakeholders. Core stack: SQL, Python/R/SAS-SPSS, Excel, Tableau/Power BI.
Java Fullstack Developer
Full-stack developer leading the migration of a legacy project from a device cloud to full cloud infrastructure, building scalable apps with Java/Spring, ReactJS, and Kafka Streams on AWS. Remote role open only to candidates in Kerala or Tamil Nadu who can join within 30 days.
Full Stack Developer IV
Leads design and development of secure, scalable web applications and services for U.S. DoD customers, working primarily in Python, FastAPI, Vue, and TypeScript, with Terraform IaC, Docker/Kubernetes, CI/CD, DevSecOps, and AI-assisted development. Requires an active Secret clearance and Security+ CE certification.
Senior MLOps Engineer
First MLOps hire at Clariti/CivCheck, building and scaling the ML infrastructure behind an AI plan-review platform for governments: end-to-end training, evaluation, and serving pipelines on cloud GPU infra, plus CI/CD, monitoring, and cost optimization for production ML. Core stack: Python, Docker, Kubernetes, AWS/GCP/Azure, MLflow/W&B/Kubeflow.