Principal ML Solutions Architect – Token Factory

This is a fully remote position, open to applicants in United States.

📋 Description

• Take charge of the most intricate and critical customer interactions, managing them from architecture through to production across various modalities while delivering measurable business impact.

• Enhance LLM inference at both the framework and hardware levels, documenting best practices into reusable team playbooks.

• Spearhead supervised and reinforcement fine-tuning initiatives to elevate model quality.

• Conceptualize and develop production-ready LLM solutions utilizing Token Factory inference services.

• Offer technical guidance in prompt engineering, RAG architectures, model selection, and analyzing cost/performance trade-offs at scale.

• Collaborate with product, engineering, and research teams to identify customer needs, prototype platform features, and shape the product roadmap.

• Assist customers in transitioning from proof of concept to production with a focus on performance, reliability, and cost-effectiveness.

• Establish standards for customer delivery and technical execution.

• Mentor Senior and mid-level Solutions Architects through review processes, enablement, and knowledge sharing.

• Represent Token Factory in external engagements, including presentations, blog posts, and conferences.

⛳️ Requirements

• Over 8 years of experience in ML/AI systems, with at least 4 years dedicated to LLMs and generative AI.

• Proven technical leadership, managing ambiguous, high-impact challenges from start to finish and influencing decisions across teams and clientele.

• In-depth expertise in the LLM ecosystem, including model architectures, fine-tuning methodologies, and inference internals.

• Extensive hands-on experience with inference optimization, covering quantization, KV-cache management, batching, and routing.

• Experience in deploying, operating, and troubleshooting LLMs in production at scale, including inference workloads down to the framework level.

• Familiarity with LLM fine-tuning practices, such as SFT/LoRA, data preparation/curation, and RL-based fine-tuning.

• Experience in creating task-specific LLM benchmarks and establishing offline/online evaluation pipelines, including LLM-as-a-judge setups.

• Knowledge of inference frameworks and libraries like vLLM, SGLang, and TensorRT-LLM, with skills in reading, modifying, and contributing to their internals.

• Experience deploying LLM-driven applications using OpenAI, Anthropic, or open-source model APIs.

• Strong proficiency in Python programming.

• Excellent communication abilities, capable of articulating technical concepts to both engineers and executives.

• Applicants must have authorization to work in the country of application and provide proof of employment eligibility.

• Added bonus: contributions or maintainership in significant OSS inference/ML projects.

• Added bonus: published research, conference presentations, or well-regarded technical writings in the LLM/serving domain.

• Added bonus: extensive experience with multimodal AI models.

• Added bonus: familiarity with Docker, Kubernetes, and infrastructure-as-code practices.

• Added bonus: experience in developing or managing internal ML workflow tools/automation at scale.

• Preferred technical skill set includes Python; vLLM, TensorRT-LLM, SGLang, Transformers, OpenAI/Anthropic SDKs; Kubernetes, Docker, Git; and AWS, GCP, and Azure ML platforms.

🏝️ Benefits

• Comprehensive company-covered medical, dental, and vision insurance for employees and their families.

• 401(k) plan with a company match of up to 4% and immediate vesting.

• 20 weeks of paid parental leave for primary caregivers and 12 weeks for secondary caregivers.

• Up to $85/month reimbursement for remote work expenses related to mobile and internet services.

• Company-paid short-term, long-term, and life insurance coverage.

• Competitive salary and compensation packages.

• Opportunities for career advancement and professional development.

• Flexibility and ownership in your role.

• A collaborative and innovative workplace culture.

• Chance to engage in impactful AI projects.

• An international environment with skilled teams.