Machine Learning Engineer – Fine-Tuning and On-device AI
Overview
HP IQ is HP’s new AI innovation lab. Combining startup agility with HP’s global scale, we’re building intelligent technologies that redefine how the world works, creates, and collaborates. We’re assembling a diverse, world-class team focused on creating an intelligent ecosystem across HP’s portfolio, developing intuitive, adaptive solutions that spark creativity, boost productivity, and enable seamless collaboration. By embedding AI advancements into every HP product and service, we’re expanding what’s possible for individuals, organisations, and the future of work.
About The Role
We are seeking a Machine Learning Engineer to lead the fine-tuning, optimization, and deployment of AI models for diverse tasks, with a strong emphasis on on-device inference . You will work on applications such as orchestration, planning, multi-agent coordination and other intelligent decision-making systems. You will adapt foundation models (LLMs, multimodal models) to specialized domains, making them fast, accurate, and efficient for resource-constrained environments while ensuring robustness and safety.
Key Responsibilities
- Model Fine-Tuning & Adaptation : Fine-tune large language models, multimodal models, and task-specific models for orchestration, planning, and related workflows.
- Experimentation : Design and run experiments to improve task accuracy, robustness, and generalization.
- Fine-Tuning Techniques : Apply methods such as full fine-tuning, LoRA, QLoRA and other parameter-efficient fine-tuning approaches.
- Model Quality : Employ techniques like QAT, DPO, and GRPO to improve model quality.
- On-Device Optimization : Prune, quantize, and compress models (e.g., INT8, INT4, mixed-precision) for CPU, GPU, NPU, and edge accelerators; optimize for low-latency inference using frameworks like OpenVINO, ONNX Runtime, QNN.
- Data Pipeline & Deployment : Build robust data pipelines for domain-specific datasets, including synthetic data generation and annotation; define evaluation metrics and perform evaluations; establish versioning and reproducibility practices.
- AI Orchestration & Planning : Develop models for multi-step reasoning, tool orchestration, and decision planning; collaborate with stakeholders on orchestrator architecture; work with product and research teams on context-aware capabilities.
Qualifications
Required :
5+ years of experience in applied machine learning, including at least 3 years in LLM fine-tuningProficiency in Python and ML frameworks (HuggingFace, PyTorch)Strong understanding of transformer architectures, attention mechanisms, and PEFT techniquesExperience with on-device inference optimization (OpenVINO, ONNX, QNN)Familiarity with orchestration / planning architectures and techniques for AI assistantsTrack record of delivering production-ready ML solutions in latency-sensitive environmentsPreferred :
Experience with multi-agent systems or AI assistant orchestrationFamiliarity with advanced inference optimization techniques such as KV cache paging and flash attentionKnowledge of inference engines (e.g., llama.cpp, vLLM)Salary Range : $120,000 - $215,000
Compensation & Benefits (Full-Time Employees)
The salary range above is indicative. Final salary is based on job-related qualifications, education, experience, knowledge, and skills. We offer a comprehensive benefits package including :
Health, dental, and vision insuranceLong-term and short-term disability insuranceEmployee assistance programFlexible spending accountLife insuranceGenerous time off, including parental leave and holidaysWhy HP IQ?
Innovative work to shape the future of intelligent computing and workplace transformationAutonomy and agility with the backing of HP’s scaleMeaningful impact by building AI-powered solutions that help people and organizations thriveFlexible work environmentForward-thinking culture and collaborative environmentEqual Opportunity Employer (EEO) Statement
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, or any other characteristic protected by law. Information disclosed voluntarily will be kept confidential. For more information, see HP’s EEO policy and rights as an applicant.
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