Top Remote Python Jobs in Atlanta, GA

Lead and grow a 5–10 engineer autonomy integration team for V-BAT/X-BAT, owning delivery, hiring, mentoring, and technical health. Drive integration of autonomy software (mission behaviors, VTOL transitions, multi-agent coordination), collaborate tightly with aircraft, perception, and capability teams, run ICDs and field tests, and support live exercises and deployments (20–30% travel).

Design, develop, and field high-performance Ground Control Station and C2 software using C++/Qt/QML and QGroundControl. Lead architecture and technical direction, mentor engineers, define APIs/ICDs, debug integration/latency issues, support field tests, implement post-mission debrief tools, and ensure interoperability with C2 standards.

Own and maintain native C++ build systems for autonomous aircraft. Improve developer velocity by reducing build/test cycle time, integrate CI with HIL and simulation, implement monitoring and alerts, troubleshoot build/test failures, and collaborate with engineers to design and deploy DevEx/DevOps solutions.

Integrate, characterize, calibrate, and validate multi-modal navigation sensors (IMUs, GNSS, cameras, altimeters). Develop test plans, calibration scripts, and data-processing tools; collaborate across electrical, mechanical, and software teams; support schematics, CAD, drivers, and lab-based sensor testing through production.

Design, implement, and deploy safety-critical navigation and state estimation systems for aerospace platforms. Develop EKF and GNSS/INS integration, multi-sensor fusion for GPS-denied environments, FDIR and integrity monitoring, and V&V test plans. Support certification, requirements allocation, performance analysis, flight test evaluation, and provide technical leadership and mentoring.

Lead design and prototyping of generative AI experiences for autonomy development; drive UX for Hivemind products; perform user research, collaborate with CTO and product leads, and deliver reference implementations and integrations across full-stack web and edge systems.

Perform finite element modeling and analyses (static, modal, fatigue, vibration) for UAV structures; validate results with hand calculations; support structural test planning, data analysis, load definition, and cross-functional design optimization to ensure lightweight, safe airframe performance.

Lead systems engineering for Hivemind-based autonomy products: define and manage requirements, develop system architectures and trade studies, coordinate hardware/software interfaces, support integration/verification/validation and testing, and identify and mitigate technical risks across the system lifecycle.

Support selection, characterization, calibration, and integration of multi-modal navigation and localization sensors (IMUs, GNSS, cameras). Develop and run test plans, calibration scripts, and data-processing tools. Work cross-functionally with EE/ME/SW on electrical interfaces, mounting, thermal/vibration, and software drivers. Debug hardware–firmware–software issues, document trade studies and integration requirements, and support production and occasional travel.

Design and implement full‑stack, low‑latency web-based Ground Control Station and C2 systems (map-centric UIs, real-time telemetry, video streaming), lead architecture and APIs, mentor engineers, support field tests and mission deployments, and ensure interoperability with C2 standards.

As a Pre-Sales Solutions Engineer, you will drive technical pre-sales engagements, architect custom solutions, and guide customers on API integration and deployment strategies, enhancing their experience with Voice AI technologies.

Design and implement secure, scalable backend services for speech inference and audio processing. Optimize networking, transcoding, latency, memory, and distributed compute orchestration. Measure and improve system performance, debug complex networking/scheduling/HPC issues, customize services for customers, and partner with Product to deliver features end-to-end.

Lead end-to-end technical integrations with enterprise healthcare customers from pre-sales through production. Scope and deliver architecture, POCs, API integrations, data mappings, and runbooks. Ensure AI/ML features meet regulatory and clinical safety standards, build reusable integration patterns, collaborate cross-functionally, and mentor junior engineers to drive successful go-lives.

The role involves providing technical leadership, hands-on execution, and cross-team influence in software engineering, focusing on solutions for scaling and performance challenges while using AI tools.

Design and build end-to-end web and AI-powered dashboard features, scale cross-platform full-stack infrastructure, standardize product patterns, mentor engineers, lead cross-team technical projects, and collaborate with product and design to improve user workflows and AI adoption.

Lead technical integrations of Cedar's platform with client healthcare systems: discover requirements, map data formats, validate data/UAT, communicate technical security and authentication needs, manage complex projects, and represent customer needs to engineering and product teams.

Provide advanced technical support for large MongoDB customers across the full MongoDB ecosystem (server, drivers, Atlas, Cloud Manager). Troubleshoot performance, architecture, recovery, security and storage issues end-to-end, develop support tools, mentor new hires, and liaise with product and engineering teams. Work EST shifts with a weekend shift expectation after ramp and participate in occasional off-hours coverage or regional events.

As a Senior Site Reliability Engineer, you'll design and build complex systems, support Atlas platform operations, automate processes, and ensure high availability of services.

Own technically complex, mission-critical areas and define technical strategy for new products. Design and ship full‑stack, AI‑driven features end‑to‑end, build scalable data ingestion and API systems, partner with product/design/customer teams to translate ambiguous problems into measurable outcomes, mentor engineers, and raise engineering quality and standards across the organization.

Technical leader for Salesforce release lifecycle: design and evolve enterprise CI/CD, automate deployments, manage cross-system releases (Salesforce, NetSuite, AWS), resolve deployment and production issues, and integrate AI-driven tooling to improve velocity, reliability, and developer self-service.

Own the technical lifecycle and operational health of a global high-density GPU fleet. Validate hardware, benchmark performance, monitor uptime and SLAs, automate operations using LLMs/agents, perform deep network and system-level troubleshooting, coordinate incident communications, and support infrastructure partners.

Design, build, and improve scalable backend systems that collect hard-to-access OSINT; build pipelines and ETL for messy data; collaborate with product and mission teams; mentor engineers and ensure reliable data delivery for DoD workflows.

Maintains and improves large-scale production systems across bare-metal servers, virtual machines, and container platforms. Responsibilities include Linux administration, architecture recommendations, hardware troubleshooting, production deployments, scripting and automation, monitoring, CI/CD, configuration management, technical documentation, and on-call support. The role collaborates with distributed cross-functional teams, uses AI to improve workflows, and requires periodic business travel and government-related background and fingerprint checks.

Validate server hardware components and new platform designs through power, thermal, performance, firmware, and automation testing. Maintain hardware test infrastructure, document technical findings, coordinate with ODM/OEM partners, and collaborate with software teams on BIOS, kernel, and firmware optimization. The role requires expertise in server architectures, validation methodologies, Linux, Python, Bash, Redfish, IPMI, and industry standards including PCIe, NVMe, and DDR.

Lead the technical vision and architecture for backend systems supporting experimentation, personalization, analytics, and conversion optimization. Design and operate high-throughput distributed systems and APIs, build data infrastructure, and productionize AI/ML capabilities. Drive complex multi-team initiatives, influence engineering strategy, establish technical standards and operational excellence, and mentor senior engineers. Partner with product, data science, ML, and engineering teams to translate business needs into scalable solutions.