Staff ML Engineer: LLM Post-Training & Deployment

Sanas; Palo Alto (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Sanas is seeking a Member of Technical Staff to lead post-training and deployment of LLMs for self-hosted, sovereign-deployed products. You will own end-to-end post-training work for text workloads, including fine-tuning, alignment, and inference optimization.

You’ll bridge customer needs with ship-ready solutions, shaping data, models, and tooling while mentoring the team and delivering measurable outcomes for high‑stakes production environments.

Qualifications

• 2+ years of experience building and deploying ML-based services in production.
• Hands-on data generation and evaluation for LLM post-training.
• Experience with SFT, instruction tuning, RLHF, or similar alignment methods.
• Strong intuition for text data quality and evaluation design.
• Experience with text post-training workflows at scale.
• Proficiency with the open-source ML ecosystem (Hugging Face, PyTorch) and modern model architectures.

Responsibilities

• Lead instruction tuning, alignment, and model optimization for real-world applications.
• Own customer post-training projects end-to-end—from requirements through data generation, training, evaluation, and delivery.
• Customize open-source models for specific customer and product needs, ensuring a seamless path from post-training to serving production workloads.
• Improve inference-time efficiency, reliability, and robustness for high-stakes, real-world deployments.
• Provide technical mentorship and guidance to the team, fostering a culture of engineering excellence and rapid innovation.

Skills

Production ML

Data generation

Model fine-tuning

RLHF/Alignment

PyTorch/Hugging Face

Tools

Kubernetes

Job description

Sanas is seeking a Member of Technical Staff to lead post-training and deployment of LLMs for self-hosted, sovereign-deployed products. You will own end-to-end post-training work for text workloads, including fine-tuning, alignment, and inference optimization.

You’ll bridge customer needs with ship-ready solutions, shaping data, models, and tooling while mentoring the team and delivering measurable outcomes for high‑stakes production environments.