Software Gigs

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 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.

As a Data Developer, you will design, develop, and maintain scalable ETL/ELT pipelines and cloud-based data platforms that integrate enterprise systems and support AI/ML initiatives for the U.S. Navy. You will perform data engineering tasks including cleansing, transformation, and optimization of SQL and Apache Spark workloads on AWS, while also developing predictive models and generative AI solutions using Python-based technologies. You will build interactive dashboards and visualizations in Tableau or Qlik, translating technical findings into actionable insights for stakeholders. An active Secret clearance, U.S. citizenship, and a bachelor's degree in a technical field (or 4+ years of relevant professional experience) are required.

Senior Software Engineer with 10+ years of experience to develop advanced algorithms and software applications using C++, Python, MATLAB, and TensorFlow in Linux environments. The role involves designing object-oriented software, prototyping AI/ML solutions, utilizing DevOps tools (GitLab, Docker, Podman), troubleshooting complex systems, and providing technical leadership to customers and internal teams. Strong mathematical foundation in probability, statistics, estimation theory, and machine learning is required to support algorithm development in a defense technology context.

Design and optimize video analysis and quality assessment algorithms for next-generation video codec hardware accelerators (FPGA/ASIC). Implement C-models and firmware for advanced video encoding, collaborating across algorithm, architecture, software, and hardware teams. Apply machine learning techniques including deep learning frameworks and transformer architectures for ROI detection, content understanding, and feature extraction. Integrate algorithms into production VOD/live streaming workflows and validate impact through A/B testing and objective quality metrics (VMAF, PSNR, SSIM).

The Applied AI Engineer develops, deploys, and maintains generative AI solutions for insurance products and internal workflows. The role involves implementing end-to-end AI pipelines using AWS services (SageMaker, Lambda, ECS/EKS, S3), building feature engineering workflows in Snowflake, and collaborating with cloud and MLOps teams. Candidates need 3+ years of AI/ML engineering experience with 1–2 years focused on generative AI or LLMs, proficiency in Python and frameworks like PyTorch or Hugging Face Transformers, and hands-on cloud deployment experience. The position requires monitoring model performance, ensuring security and compliance, and supporting AI architecture reviews.

Qualcomm seeks a Machine Learning R&D leader to design and deliver Agentic AI systems for hardware design automation. The role combines hands-on technical execution with team leadership, requiring deep expertise in generative AI, large language models, and ML/AI product development. Responsibilities include architecting end-to-end ML solutions, coaching an interdisciplinary team of researchers and engineers, and bridging research prototypes into production design tools. The ideal candidate brings PhD-level credentials, 2+ years of industry ML/GenAI experience, and proven expertise in agentic AI frameworks, foundation models, and complex ML software pipelines.

Design and optimize video analysis, quality assessment, and encoding algorithms for hardware-accelerated video codec solutions (FPGA/ASIC). Develop C-models and firmware for real-time video processing, implementing algorithms for ROI detection, content understanding, frame-level rate control, and objective quality metrics. Collaborate with infrastructure and platform teams to integrate algorithms into production VOD and live-streaming workflows, validate performance through A/B testing, and optimize end-to-end video quality. The role requires strong programming skills in C/C++ or Python, knowledge of video quality standards (VMAF, PSNR, SSIM), and ideally experience with deep learning frameworks, video codecs, or embedded real-time systems.

As a client-facing data analyst, you'll work with Department of the Navy clients to understand their data needs, transform complex structured and unstructured data into actionable insights, and advise on how findings impact DoD acquisition programs and IT modernization. You'll use tools like Tableau, Python, R, or SQL for data manipulation; Databricks or Spark for data engineering; and Power Apps/Power Automate for automation. You must hold or be able to obtain a Secret clearance and have 4+ years of DoD client experience.

Senior Software Engineer/Research Scientist applying advanced mathematical and algorithmic expertise to defense technology development. Responsibilities include algorithm development in probability, statistics, estimation theory, machine learning, and optimization; designing and maintaining C++ software applications in Linux environments; prototyping AI/ML solutions in MATLAB, Python, and TensorFlow; and managing DevOps workflows using GitLab, Docker, and Podman. Requires 10+ years of engineering experience, a B.S. in engineering/mathematics, and ability to obtain a DoD Secret clearance.

As an AI Software Engineer at Qualcomm, you will develop and optimize machine learning software for the Qualcomm AI Stack (QAIRT and Genie SDKs), enabling efficient execution of large language models and deep neural networks on Snapdragon platforms. You will validate and optimize performance of generative AI models, debug complex issues, and collaborate across teams to deliver robust AI solutions. The role requires strong software design, programming, and debugging skills, with expertise in machine learning frameworks, embedded systems optimization, and languages like Python or C++. You will work with minimal supervision, participate in design reviews, and contribute to a culture of technical excellence.