The Commercial Systems Software team is in search of a driven individual who can design comprehensive advanced technology solutions to support the organization's strategic goals and objectives, with a particular emphasis on the integration of AI models (e.g., LLMs, Classification, RL, etc.) into AI PCs. The role involves developing innovative technological solutions that facilitate the efficient scaling of strategic initiatives across business units. A strong focus on secure software development and operational excellence is required, utilizing Agile methodologies to create solutions that differentiate us in the market. **Key** **Responsibilities:** + Plays a leading role in development of AI integration projects while aligning them with business and security strategies and requirements. + Leads the building of standards, designs, automation, and the deployment of software within the context of AI model integration in production environments. + Designs and develops end to end solutions that protects and manage AI integration software products and data. + Drives technology strategy and engineering roadmaps around AI integration software engineering, ensuring scalability, efficiency, secure data communication, and alignment with business objectives. + Assists supervisors with project development, including documentation of features, recording of progress, and creation of the testing plan. + Converts business concepts into the next generation of applications and tools, utilizing adaptive agile methodologies to deliver a minimal viable product to the business. + Provides mentorship and technical guidance to software development team. + Works closely with cross-functional teams, including product management and design, to drive product and software features from concept to deployment. + Contributes innovative ideas and exercising independent judgment to solve unique and complex problems impacting the business. **Education & Experience Recommended:** + Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or a related discipline, equivalent work experience. + Typically has 12+ years of industry experience, with a proven track record in AI/ML engineering, AI model integration, optimization, and large-scale software development, particularly within AI-driven application and hardware systems. **Preferred Certifications** + Programming Language/s Certification (Java, C++, Python, JavaScript, or similar) **Knowledge & Skills:** **_Core_** **_AI/ML/DL/RL Expertise_** + Comprehensive knowledge of machine learning (ML), deep learning (DL), and reinforcement learning (RL) techniques, with proven experience in deploying ML, DL, and RL models into production-grade environments, ensuring high performance, scalability, and reliability. **_LLM-Specific Skills_** + Proficiency in LLM fine-tuning using state-of-the-art techniques, such as: + Parameter-Efficient Fine-Tuning (PEFT). + LoRA (Low-Rank Adaptation) adapters and prompt tuning. + Merge techniques like superposition and weight merging to optimize LLM performance across variants. + Strong expertise in retrieval-augmented generation (RAG) workflows, including: + Building and managing vector databases (e.g., Pinecone, FAISS, Weaviate, Qdrant) for knowledge retrieval. + Integrating knowledge retrieval systems into LLM pipelines. + Implementing agentic workflows for task automation using tools like LangChain or LlamaIndex. + Experience in designing and deploying agent-based systems with autonomous task execution and reasoning. + Multi-model workflow development and integration experience **_AI/ML Frameworks and Tools_** + Proficiency in data preprocessing, training, and fine-tuning models using frameworks such as: + TensorFlow, PyTorch, and lightweight inference frameworks: ONNX, OpenVINO, QNN, TensorFlow Lite, Libtorch. + Specialized tools: Hugging Face Transformers, Keras, Scikit-learn, JAX. + Expertise in distributed training techniques leveraging tools like Horovod, Ray, or Dask. + Experience with Unsloth for debugging and optimizing model latency and throughput during inference workflows. **_MLOps Skills_** + Advanced skills in MLOps practices to support AI/ML pipelines, including: + Model versioning and tracking: MLflow, Weights & Biases + CI/CD pipelines for ML workflows: Kubeflow, Vertex AI, SageMaker Pipelines, Airflow. + Proficiency in containerization and orchestration, including: + Docker: Containerizing AI/ML applications with complex dependencies. + Kubernetes (K8s): Deploying, scaling, and managing ML workflows in distributed systems. + Helm: Packaging and deploying Kubernetes applications. + Experience in implementing microservices architectures for modular, scalable, and interoperable AI/ML solutions. **_Programming and Development Skills_** + Proficiency in Python for Data Science and at least two of the following languages: + C++, C#, C, Java, or Rust. + Experience with on-edge inference techniques and deploying models across diverse environments, including cloud, on-prem, and edge devices. + Hands-on experience with application development using frameworks like: + UWP, WPF, WinUI3, WebView2, React Native, or equivalent. **_AI-Powered System Integration_** **_Skills_** + Expertise in integrating AI solutions within AI-powered PCs or edge devices, ensuring performance optimization at the hardware-software interface level. + Familiarity with hardware accelerators (e.g., TPUs, GPUs, MPUs) for efficient AI model training and inference. **_Soft Skills and Collaboration_** + Strong ability to collaborate across engineering, product, and data science teams to deliver end-to-end AI solutions. + Exceptional problem-solving and analytical skills, with a focus on designing scalable and impactful AI-driven applications. **Cross-Org Skills** + Strong leadership, results driven and excellent verbal and written communication skills, with the ability to convey technical concepts to non-technical stakeholders. + Self-motivated with strong analytical and problem-solving skills, with the ability to tackle complex AI challenges creatively. + Advanced learning agility and digital fluency + Customer driven **Impact & Scope** + Impacts key strategic AI initiatives across the business, driving AI model innovation and integration at the enterprise level. Leads cross-functional teams and projects that span multiple business units. **Complexity** + Provides highly innovative and strategic solutions to complex challenges, directly shaping the future of AI initiatives and their integration into next-generation products. The base pay range for this role is $ 154,000.00 to 223,300.00 annually with additional opportunities for pay in the form of bonus and/or equity (applies to US candidates only). Pay varies by work location, job-related knowledge, skills, and experience. **Benefits:** HP offers a comprehensive benefits package for this position, including: + Health insurance + Dental insurance + Vision insurance + Long term/short term disability insurance + Employee assistance program + Flexible spending account + Life insurance + Generous time off policies, including; + 4-12 weeks fully paid parental leave based on tenure + 11 paid holidays + Additional flexible paid vacation and sick leave (US benefits overview (https://www8.hp.com/h20195/v2/getdocument.aspx?docname=c07065756) ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.