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

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.

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Remote Work :

Yes

Employment Type :

Full-time