Senior ISV AI Technical Architect
TEX01 - Houston, Texas (TEX01), United States
HP
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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)
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.
Job -
SoftwareSchedule -
Full timeShift -
Shift 1, 0% premium (United States of America)Travel -
Relocation -
Equal Opportunity Employer (EEO) -
HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).
Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.
If you’d like more information about HP’s EEO Policy or your EEO rights as an applicant under the law, please click here: Equal Employment Opportunity is the Law Equal Employment Opportunity is the Law – Supplement
Tags: Agile Airflow Architecture CI/CD Classification Computer Science Deep Learning Distributed Systems Docker Engineering FAISS Helm Horovod Java JavaScript JAX Keras Kubeflow Kubernetes LangChain LLMs LoRA Machine Learning Microservices MLFlow MLOps Model training ONNX Pinecone Pipelines Python PyTorch RAG React Reinforcement Learning Rust SageMaker Scikit-learn Security TensorFlow Testing Transformers Vertex AI Weaviate Weights & Biases
Perks/benefits: Career development Equity / stock options Flex hours Flexible spending account Flex vacation Health care Insurance Medical leave Parental leave Salary bonus
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