Principal Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home in San Francisco

Energy Jobline ZR; San Francisco (CA); Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Medical insurance

Dental

Vision

PTO

Savings Plan

Job summary

Energy Jobline ZR is seeking a Principal Machine Learning Engineer to architect and optimize large‑scale ML systems. This is a 100% remote role, guiding training, inference, evaluation, and infrastructure with a focus on scalable, reliable production deployments.

You will own end‑to‑end ML pipelines, including GPU‑based optimization and latency‑aware inference, while collaborating with backend, mobile, and desktop teams to ship impactful AI features.

Qualifications

• Strong background in deep learning and transformer‑based architectures.
• Hands‑on experience training, fine‑tuning, or deploying large‑scale ML models in production.
• Proficiency with modern ML frameworks (PyTorch, JAX) and ability to learn others quickly.
• Experience with distributed training and inference frameworks (DeepSpeed, Megatron, Ray).
• Strong software engineering fundamentals; production‑grade systems.

Responsibilities

• Architect and build large‑scale ML systems across data, training, evaluation, inference, and deployment.
• Design high‑performance training pipelines on GPU infrastructure.
• Architect inference systems balancing latency, throughput, cost and reliability.
• Own production deployment including GPU optimization and memory efficiency.
• Collaborate with engineering to integrate ML systems into products.

Skills

Deep learning

Transformer architectures

PyTorch

JAX

Distributed training/inference

GPU optimization

RLHF pipelines

Tools

DeepSpeed

Megatron

Ray

TensorRT

Job description

Principal Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home

As a Principal Machine Learning Engineer, you are a deep technical authority responsible for designing and evolving the most critical ML systems in the company. The Principal Machine Learning Engineer will operate across training, inference, evaluation, and infrastructure, solving the hardest architectural and performance problems. While Technical Leads may own execution at the team level, you set the technical standard and shape how ML systems are built across the organization. This is a hands‑on, high‑impact role focused on depth.

This position is 100% Remote.

Principal Machine Learning Engineer Responsibilities:

• Architect and build large-scale ML systems spanning data, training, evaluation, inference, and deployment.
• Design reproducible, high-performance training pipelines across GPU infrastructure.
• Architect inference systems that balance latency, throughput, cost, and reliability at scale.
• Design and maintain data systems for high-quality synthetic and real-world training data.
• Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.
• Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.
• Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products.
• Make pragmatic trade‑offs and ship improvements quickly, learning from real usage.
• Work under real production constraints: latency, cost, reliability, and safety

Principal Machine Learning Engineer Outcomes:

• ML systems (training, inference, evaluation) are reliable, scalable, and meet defined performance targets.
• Models deployed to production achieve measurable quality improvements and meet user‑impact goals.
• Production issues are proactively monitored, debugged, and resolved with clear root‑cause analysis.
• Team and cross‑functional collaborators benefit from clear guidance, best practices, and scalable ML solutions.
• Research‑to‑production cycles are efficient, safe, and continuously improve the product experience.

Qualifications

Principal Machine Learning Engineer Qualifications:

• Strong background in deep learning and transformer‑based architectures.
• Artificial Intelligence (AI) experience required.
• Hands‑on experience training, fine‑tuning, or deploying large‑scale ML models in production.
• Proficiency with at least one modern ML framework (e.g. PyTorch, JAX), and ability to learn others quickly.
• Experience with distributed training and inference frameworks (e.g. DeepSpeed, FSDP, Megatron, ZeRO, Ray).
• Strong software engineering fundamentals; you write robust, maintainable, production‑grade systems.
• Experience with GPU optimization, including memory efficiency, quantization, and mixed precision.
• Comfort owning ambiguous, zero‑to‑one ML systems end‑to‑end.
• A bias toward shipping, learning fast, and improving systems through iteration.
• Experience with LLM inference frameworks such as vLLM, TensorRT‑LLM, or FasterTransformer.
• Contributions to open‑source ML or systems libraries.
• Background in scientific computing, compilers, or GPU kernels.
• Experience with RLHF pipelines (PPO, DPO, ORPO).
• Experience training or deploying multimodal or diffusion models.
• Experience with large‑scale data processing (Apache Arrow, Spark, Ray).

Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.

Keywords: San Francisco CA Jobs, Principal Machine Learning Engineer, Apache Arrow, DeepSpeed, DPO, FasterTransformer, FSDP, GPU Kernels, JAX, LLM, Machine Learning, Megatron, ML, ORPO, PPO, Principal Machine Learning Engineer, Pytorch, RLHF Pipelines, Spark, TensorRT-LLM, Virtual Large Model, vLLM, Work From Home, ZeRO Ray, California Recruiters, IT Jobs, California Recruiting