Software Gigs

Senior Site Reliability Engineer responsible for designing and implementing Infrastructure as Code solutions, managing containerized and serverless architectures, and driving automation to reduce operational toil across large-scale production systems. The role requires defining Service Level Objectives (SLOs), leading incident response efforts, implementing monitoring and logging systems, and collaborating with development teams to ensure reliability and scalability. Requires 5+ years of SRE or cloud engineering experience with deep expertise in Terraform, CloudFormation, Docker, Kubernetes, CI/CD pipelines, and cloud security practices. Must be a US citizen eligible to obtain and maintain an active Secret security clearance or above.

This role involves evolving Qualcomm's Robotic Process Automation capabilities into next-generation agentic automation solutions. The Senior Agentic Automations Engineer will design and deploy AI-driven agents, enterprise chatbots, and workflow engines, leading technical delivery across a global team while integrating RPA platforms like Automation Anywhere with containerized architectures. Key responsibilities include defining automation standards, building full-stack enterprise applications, and ensuring secure integration with enterprise systems using Docker, Kubernetes, and agentic frameworks like LangGraph and n8n.

Tesla seeks an embedded software engineer to develop firmware for cell formation manufacturing systems. The role involves writing embedded C and Python code for real-time controls, battery management algorithms, power conversion, and functional safety across prototyping through high-volume production. You will collaborate with manufacturing and electrical engineering teams on hardware bring-up, system validation, and production integration. The position requires proficiency in C/C++, embedded protocols (CAN, UDS, etc.), and a strong foundation in electrical engineering concepts and software fundamentals.

This Embedded Software Engineer role at Leidos involves designing and developing high-performance embedded software for custom System-on-Chip (SoC) hardware in electronic warfare applications. You will write low-level C/C++ code for multi-core systems (DSP, ARM, RISC-V), perform hardware-software co-design and validation, and build software development kits for end users. The position requires 4+ years of embedded systems experience, deep understanding of hardware architectures, and proficiency in reading datasheets, test-driven development, and real-time operating systems.

Senior Embedded Software Engineer role focused on R&D and production software development for next-generation radar products. Responsibilities include building embedded Linux systems, supporting system integration on custom hardware, and maintaining deployed software for U.S. and international defense customers. Requires 4+ years of professional object-oriented software development with C/C++ and Python, extensive Linux experience, and familiarity with Agile/Scrum methodologies. Must be a U.S. Person with ability to access U.S.-only data systems.

Build emulation frameworks and tools for cyber-physical systems, extending platforms like QEMU in C/C++ and Python to support new embedded architectures (ARM, PPC, etc.). Rehost and reverse-engineer unknown firmware by analyzing binaries and hardware dependencies, then develop virtual device models and digital simulations validated against real hardware behavior. Work within a small focused team on architecture, implementation, testing, and technical documentation of modular emulation software.

Qualcomm is seeking a software engineer to develop power and limits management software for SoC chipsets, owning the full lifecycle from pre-silicon through commercialization. The role involves analyzing requirements, designing robust software solutions, optimizing for power efficiency, and developing profiling/validation tools across multiple subsystems. Candidates will perform detailed analysis to recommend improvements in performance, memory, and power utilization, including algorithm design and SW/HW partitioning. The position requires hands-on embedded systems expertise, real-time OS knowledge, and the ability to interface across system, power, software, and hardware engineering disciplines.

Design, develop, and optimize machine learning systems for production AI platforms, including model development, inference optimization, and scalable ML infrastructure. Build training-to-deployment pipelines, optimize model serving for latency and cost, and integrate LLMs and generative AI models into microservices and APIs. Develop data pipelines for ingestion, preprocessing, and feature engineering while collaborating cross-functionally with product, platform, and hardware teams to deliver end-to-end ML solutions.

As a SW Test Development Engineer 2, you will design and build automation tools and frameworks to test Dexcom's continuous glucose monitoring devices and mobile apps (iOS/Android). You will develop in Python or Java to create testing APIs, integrate tools like Jira, Testrail, Slack, and GitHub, and manage end-to-end test suites in CI/CD pipelines. The role requires 2–3 years of software development experience with object-oriented languages, hands-on familiarity with cloud platforms (AWS/GCP), containerization (Docker), and embedded/mobile device automation.

Senior Software Engineer working within the Knowledge Exploitation & Decisions Systems Group to build scalable microservices and high-performance APIs for command & control, trusted AI, and advanced reasoning systems. You will take technical ownership of features within a mature mission planning solution, translating complex mathematical models from PhD scientists into production-grade software. Required: 5+ years (BS) or 1-2+ years (MS) of professional experience building maintainable APIs; strong proficiency in Java 17+, Spring Boot, and object-oriented design patterns; experience with Linux, Docker, Kubernetes, and DevSecOps practices.

Lead ADAS R&D software engineering efforts for autonomous vehicle perception and decision systems at Qualcomm. Design, develop, and optimize embedded software blocks including deep-learning-based camera perception, lidar/radar perception, multi-sensor fusion, object tracking, behavior prediction, trajectory planning, and vehicle control. Develop efficient middleware for sensor data sharing and SDKs enabling customer proof-of-concepts. Requires Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or related field plus 7 years of related experience.

Lead a specialized team of software engineers developing innovative Pixel sensor experiences at the intersection of hardware, software, and AI. You will drive the design and implementation of real-time embedded systems that process sensor signals efficiently while applying machine-learning and signal-processing algorithms in a power-optimized manner. Required: 8 years software development experience, 5 years in computer vision or signal processing, 5 years leading ML design and infrastructure optimization, and 3 years technical leadership. This role demands deep expertise in embedded software, AI/ML algorithms, sensor fusion, and the ability to independently architect systems while managing a team.

As a Senior Systems Engineer for Data Center AI at Qualcomm, you will research, develop, optimize, and validate AI/ML solutions that integrate Qualcomm's hardware accelerators with software and ecosystem to deliver high-performance inference in datacenter environments. You will design and deploy Gen AI and LLM applications, implement fine-tuning and distillation techniques, perform model benchmarking, and drive system-level architecture decisions. You will collaborate across functional teams to meet system-level requirements while staying current with advances in AI/ML models and hardware. Required skills include strong Python proficiency, expertise in ML frameworks (PyTorch, TensorFlow), deep understanding of ML deployment and system performance profiling, and experience with parallel computing.

Own and deliver small to medium machine learning system components from design through production deployment, including building data pipelines, training and evaluating models, and implementing MLOps monitoring. Write high-quality Python code to translate technical requirements into maintainable solutions, working with frameworks like scikit-learn, TensorFlow, PyTorch, and HuggingFace. Design and deploy ML models as microservices, APIs, batch jobs, or streaming components on AWS, with responsibility for model performance metrics, data drift detection, and retraining triggers. Collaborate across Data Engineers, Software Engineers, Data Scientists, and product stakeholders to deliver project objectives.

Join Qualcomm's Enterprise AI Engineering organization as a BizAI Tech Functional Engineer, bridging business stakeholders in Finance, Sales, and SCM with the AI engineering team. You will design and deliver AI-driven agents, natural-language analytics, and workflow automations on Qualcomm's unified BizAI platform, integrating with enterprise systems like Databricks, Oracle, Salesforce, and M365. The role requires full-stack technical expertise (Python, TypeScript, FastAPI, n8n, Kubernetes) combined with functional fluency to translate process pain points into governed, production-grade solutions that meet SOX, security, and auditability standards. You'll support adoption through enablement and hands-on guidance while defining standards for scalability and compliance across the enterprise.

As a Staff Graphics Software Engineer, you will architect, design, implement, and optimize GPU hardware, drivers, features, and tools for next-generation gaming, XR, and AI experiences. You will write complex code in C++, C, Perl, and Python across simulation, emulation, and on-device environments, develop comprehensive pre- and post-silicon tests, and collaborate with cross-functional teams and external stakeholders. The role requires 4+ years of relevant software/hardware engineering experience (or equivalent with advanced degree) and deep graphics and GPU expertise. You will work independently with minimal supervision while providing guidance to team members and influencing key organizational decisions.

Senior Firmware Engineer role focused on developing and optimizing low-level embedded software in C++ for flight-critical avionics and unmanned aerial systems (UAS). You will port frameworks to new RTOSes and hardware platforms, create Board Support Packages and Hardware Abstraction Layers for ARM Cortex-M architectures, develop peripheral drivers (I2C, SPI, UART, ADC, wireless), and conduct unit/integration testing including MISRA C compliance checks. You'll diagnose cross-domain issues across electromechanical, software, networking, and RF subsystems, and translate mission requirements into technical specifications and test documentation.

Senior embedded software engineer role developing mission-critical firmware for Amazon's Leo satellite constellation. Responsibilities include architecting ASIC firmware, RF communication subsystems, secure boot operations, real-time embedded software, and hardware interfaces using protocols like I2C, SPI, UART, and Ethernet. The role requires security-by-design principles, threat modeling, secure coding practices, and collaboration with hardware architects and systems engineers to bring custom silicon from concept through secure bring-up and production integration.

Design and build software to automate RF hardware test systems for satellite components before flight, including test infrastructure, CI/CD automation, and production-scale testing orchestration. Write Python on Linux test racks to measure satellite modem, amplifier, and RF component performance against pass/fail thresholds, translating hardware engineer requirements into reliable automated test logic. Support manufacturing validation, on-orbit failure analysis, and enable factory operators to run environmental stress testing at scale. Own software quality, release processes, and work with SCPI-controlled test instruments, thermal chambers, and telemetry dashboards that drive ship/no-ship decisions.

Design, implement, and maintain secure DevSecOps automation frameworks across on-premise and cloud infrastructure, integrating security controls into CI/CD pipelines for application and configuration deployment. Develop Infrastructure as Code using Terraform, Ansible, ARM/Bicep, PowerShell, Python, and Bash across Windows, Linux, VMware, Azure, and hybrid environments. Automate provisioning, patching, vulnerability remediation, and compliance checks aligned with FFIEC, NCUA, CIS, and NIST standards while partnering with Cybersecurity, Infrastructure, and Application Development teams. Support container/platform engineering, cloud identity governance, and promote DevSecOps and GitOps practices across technology teams.

The Database Engineer will maintain, monitor, and optimize large-scale production MySQL database environments in distributed, mission-critical settings. Responsibilities include performance tuning, query and index optimization, database migrations and upgrades, capacity planning, and 24x7 on-call support. The role requires designing reliable database architectures, automating operational tasks, and collaborating with development teams on database design guidance. Candidates must have strong fundamentals in distributed database topologies, Linux administration, scripting proficiency (Go/Python/Shell), and experience with cloud platforms such as Azure.

Senior Python Backend Engineer building and maintaining Python-based APIs and services in an AWS environment. The role focuses on developing Kafka-based data pipelines, managing data movement across systems, and ensuring reliability and performance of containerized services. You'll need strong production Python experience, familiarity with streaming or message-based systems, and comfort working with AWS and Docker.

Own the complete release and deployment strategy for Elemynt's secure AI infrastructure platform, building systems that ensure every release is versioned, reproducible, observable, and safe to operate across enterprise and scientific computing environments. Design and implement deployment automation, CI/CD pipelines, artifact management, and operational visibility (logs, metrics, alerts) that work reliably in customer-managed and restricted environments. Debug incidents, identify root causes, and systematize fixes into reusable automation. Partner with product and engineering teams to embed deployment readiness into the platform from the start.

Design and own cloud infrastructure foundations, core platform services, and observability systems that enable reliable deployment across customer environments (on-premise, cloud, or hybrid). Build production-grade Kubernetes infrastructure, internal APIs, deployment pipelines, and monitoring/alerting layers using infrastructure-as-code. Instrument service-level objectives and health signals to ensure measurable reliability and reproducible, secure deployments across all environments.

Build and operate the data and ML infrastructure powering an AI platform for materials science, owning both sides: data pipelines that ingest and curate large-scale scientific output into training-ready formats, and model packaging, serving, monitoring, and CI/CD systems that move models safely from research to production across customer environments. You will design data ingestion and transformation workflows, implement validation and quality gates, package and version models with reproducible builds, run models through batch and online inference with safe rollout and rollback, monitor for drift and degradation, and build observability and internal tooling for engineering and science teams. The role requires 6+ years shipping production software with deep expertise in data systems, ML infrastructure, containers, orchestration, and observability.