Preference optimization jobs

Sr Principal Security Researcher – AI (Cybersecurity LLM Post-Training, Evals, and Environments)

Palo Alto Networks · Posted Sep 9, 2026

Open

Santa Clara, United States
On-site
Full-time · Senior
$163K–$264K per year

Sr Principal Security Researcher – AI (Cybersecurity LLM Post-Training, Evals, and Environments)

Palo Alto Networks · Posted Sep 9, 2026

Open

Santa Clara, United States
On-site
Full-time · Senior
$163K–$264K per year

Principal Product Manager, Model Customization & Open-Weight Models

Equinix · Posted Nov 4, 2026

Open

Redwood City, California, United States
Full-time · Senior
7+ years

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Designs, develops and manages the lifecycle of a product or group of products from concept to launch to end of life, focusing on model selection, customization, and open-weight or proprietary models.

Responsibilities

Own model selection: define how Equinix chooses models for each application based on quality, cost, latency, context length, tool-use, hardware footprint, and licensing.
Maintain a recommended-model catalogue across open-weight and proprietary models.
Track new-model releases and benchmark them against Equinix workloads.
Lead model customization: set the playbook for adapting models (prompt/context engineering, fine-tuning, LoRA, preference optimization, RLHF, distillation, quantization).
Define the data strategy behind tuning (curation, labeling, synthetic data generation, deduplication).

Requirements

Computer Science
Engineering
Machine Learning
Quantitative field
Nice to have: Reinforcement learning from human or AI feedback (RLHF)

Skills

Product Management AI/ML Data platforms Infrastructure platforms

AI Phone - Applied ML / Model Engineer

Bjak · Posted Nov 4, 2026

Open

Seoul, Korea

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Apply machine learning techniques to develop and fine‑tune large language models for AI phone use cases.

Responsibilities

Evaluate foundation models against phone use cases
Identify capabilities handled by existing models and where adaptation is needed
Experiment with SFT, LoRA/QLoRA and other fine‑tuning techniques
Improve model performance for intent recognition, instruction following, tool calling, structured outputs, and multi‑step task execution
Explore synthetic data generation and dataset construction for phone‑specific workflows

Requirements

Nice to have: agentic systems
Nice to have: function calling
Nice to have: tool‑use training
Nice to have: synthetic data generation
Nice to have: preference datasets

Skills

Machine Learning Deep Learning NLP LLMs open‑weight models model fine‑tuning

AI Phone - Applied ML / Model Engineer

Bjak · Posted Nov 4, 2026

Open

China

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Responsibilities

Evaluate existing foundation models (e.g. Qwen, Llama, Gemma and other suitable open-weight models) against our target phone use cases.
Identify which capabilities can be handled by existing models and where additional model adaptation or fine-tuning is needed.
Experiment with SFT, LoRA/QLoRA and other lightweight fine-tuning techniques for specific use cases.
Improve model performance for intent recognition, instruction following, tool calling, structured outputs, and multi-step task execution.
Explore synthetic data generation and dataset construction for phone-specific workflows.

Requirements

Nice to have: agentic systems
Nice to have: function calling
Nice to have: tool-use training
Nice to have: synthetic data generation
Nice to have: preference datasets

Skills

Machine Learning Deep Learning NLP LLMs open-weight models

Research Scientist Intern, Generative Recommendation (PhD)

Meta · Posted Nov 4, 2026

Open

Singapore, Singapore
On-site
Internship · Intern

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Conduct research on generative recommendation systems, develop models, and collaborate with researchers and engineers to advance personalized retrieval and ranking.

Responsibilities

Conduct research on generative recommendation, including autoregressive transformers, diffusion models, and flow matching for personalized retrieval and ranking
Explore multimodal modeling approaches that combine images, video, text, and user interaction histories to learn content representations and user preferences
Develop reinforcement learning, reward modeling, and preference optimization methods to improve recommendation quality and long-term user satisfaction
Design, implement, and evaluate novel model architectures and training algorithms through rigorous experimentation
Collaborate closely with researchers and engineers to translate research ideas into scalable recommendation methods

Requirements

Ph.D. in Computer Science, Electrical Engineering, or a related field

Skills

Python PyTorch LLMs computer vision diffusion models

Machine Learning Engineer - New Grad

SambaNova Systems · Posted Nov 3, 2026

Open

Austin, Texas, United States +1 more
Entry
$131K–$197K per year
0+ years

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As a new grad Machine Learning Engineer, you’ll train and evaluate models that make large language models cheaper and more capable to serve.

Locations (2)

Austin, Texas, United States
San Jose, California, United States

Compensation

$131,200—$196,800 USD

Responsibilities

Train, evaluate, and tune speculative decoding models to increase acceptance rates on production workloads.
Develop and implement optimization techniques, including quantization, sparsity, distillation, pruning, and parameter-efficient fine-tuning, to quantify the trade-offs between model quality, latency, and resource efficiency.
Build and evaluate agentic systems: tool calling, multi-step planning, retrieval, and long-context reasoning on top of our serving stack.
Design rigorous evaluations and benchmarks; make accuracy and quality claims that hold up under scrutiny
Translate recent research into working implementations, and run ablations to understand what actually drives the result

Sr Principal Security Researcher – AI (Cybersecurity LLM Post-Training, Evals, and Environments)

Sr Principal Security Researcher – AI (Cybersecurity LLM Post-Training, Evals, and Environments)

Compensation

Responsibilities

Requirements

Skills

Principal Product Manager, Model Customization & Open-Weight Models

Responsibilities

Requirements

Skills

AI Phone - Applied ML / Model Engineer

Responsibilities

Requirements

Skills

AI Phone - Applied ML / Model Engineer

Responsibilities

Requirements

Skills

Research Scientist Intern, Generative Recommendation (PhD)

Responsibilities

Requirements

Skills

Machine Learning Engineer - New Grad

Locations (2)

Compensation

Responsibilities

Benefits

Requirements

Skills

Benefits