Ai Lab – Senior Ml Engineer, Model Optimization

hace 1 mes

Barcelona, España Hewlett Packard A tiempo completo

Job Summary
The AI Lab is responsible for bringing state-of-the-art research in Generative AI (and AI in general) to the Personal Systems (PS) product portfolio to solve top user needs and enable all new type of user experiences. The team will be in two main locations: Sant Cugat (ESP) and Palo Alto (US).
In this context, we are looking for a Senior Machine Learning Engineer that would help drive key initiatives in this space, especially focusing on optimizing models and deploying them in constraint HW including memory-bound environments and on CPU, xGPU and NPU. You will work closely with different teams across the organization to support their modeling needs, translating high level user needs to specific modeling requirements, creating plans and technically driving the team to execute on those.
Responsibilities

Focus on model optimization and deployment, exploring and implementing strategies that allow reducing memory footprint and improve latency, without a significant impact on model quality.
Help define the technical roadmap of the AI lab with the goal of supporting HP's ambitious AI roadmap.
Define and develop processes and standards to ensure that the team is building high quality and safe models.
Adopt state-of-the-art Gen AI modeling and evaluation techniques.
Execute strategic engineering proof of concepts in the Gen AI space.
Partner closely with key stakeholders across functions including product and design leads and help define the overall AI strategy.
Mentor more junior team members.

Education & Experience Recommended

Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence. Master's or PhD in AI or related area will be highly valued.
Typically has 7+ years of work experience on AI modeling or applied ML.

Knowledge & Skills

Training and fine-tuning of LLMs / LMMs.
Data acquisition and preprocessing.
Model lifecycle management.
Software development.
Programming languages (e.g., Python, C++, Java).

Cross-Org Skills

Effective Communication
Results Orientation
Learning Agility
Digital Fluency
Customer Centricity

Impact & Scope
Influences HP's long term AI strategy, one of the top investment areas for HP.

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