HP IQ
Machine Learning Engineer – Fine-Tuning and On-device AI
HP IQ, Palo Alto, California, United States, 94306
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-tuning
Proficiency in Python and ML frameworks (HuggingFace, PyTorch)
Strong understanding of transformer architectures, attention mechanisms, and PEFT techniques
Experience with on-device inference optimization (OpenVINO, ONNX, QNN)
Familiarity with orchestration/planning architectures and techniques for AI assistants
Track record of delivering production-ready ML solutions in latency-sensitive environments
Preferred:
Experience with multi-agent systems or AI assistant orchestration
Familiarity with advanced inference optimization techniques such as KV cache paging and flash attention
Knowledge 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 insurance
Long-term and short-term disability insurance
Employee assistance program
Flexible spending account
Life insurance
Generous time off, including parental leave and holidays
Why HP IQ?
Innovative work to shape the future of intelligent computing and workplace transformation
Autonomy and agility with the backing of HP’s scale
Meaningful impact by building AI-powered solutions that help people and organizations thrive
Flexible work environment
Forward-thinking culture and collaborative environment
Equal 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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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-tuning
Proficiency in Python and ML frameworks (HuggingFace, PyTorch)
Strong understanding of transformer architectures, attention mechanisms, and PEFT techniques
Experience with on-device inference optimization (OpenVINO, ONNX, QNN)
Familiarity with orchestration/planning architectures and techniques for AI assistants
Track record of delivering production-ready ML solutions in latency-sensitive environments
Preferred:
Experience with multi-agent systems or AI assistant orchestration
Familiarity with advanced inference optimization techniques such as KV cache paging and flash attention
Knowledge 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 insurance
Long-term and short-term disability insurance
Employee assistance program
Flexible spending account
Life insurance
Generous time off, including parental leave and holidays
Why HP IQ?
Innovative work to shape the future of intelligent computing and workplace transformation
Autonomy and agility with the backing of HP’s scale
Meaningful impact by building AI-powered solutions that help people and organizations thrive
Flexible work environment
Forward-thinking culture and collaborative environment
Equal 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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