Applied AI Engineer
Job description
About the role
You will own advisory engagements that translate artificial intelligence strategy into production outcomes for customers across a global landscape. Your work will serve as the vital bridge connecting research scientists and executive leadership to ensure alignment on technical and business objectives. At the Staff or Principal level, you will interact with PhD-level data scientists while simultaneously articulating return on investment to chief executives. This position demands a hybrid profile that functions as part scientist, part consultant, and part communicator. The role is distinctly not a standard back-end engineering position focused solely on code maintenance. It involves high-level pre-sales architecture and advisory responsibilities that require a global mindset and strategic foresight. You will expand your impact in direct relation to company growth and market penetration. You will operate within shifting contexts and ambiguous environments, navigating complexity to deliver clear pathways for AI adoption.
Key facts
Location is Remote within the United States.
Engagement requires 30-60% travel with global collaboration.
The compensation range is Base 180,000 USD to 220,000 USD annually.
What you'll do
- Lead technical discovery sessions to identify high-value AI use cases specific to client data and industry verticals.
- Architect inference and training workflows, including optimization for NVIDIA and AMD clusters deployed within Kubernetes environments.
- Translate complex research findings into field content that guides partners through qualification and enablement processes for enterprise AI adoption.
- Represent Everpure at industry conferences and partner forums to build technical credibility and strengthen our reputation.
- Orchestrate cross-team initiatives that span solutions, sales, and alliances to align campaigns and accelerate deal closure.
- Operate independently through the full lifecycle of exploration, scoping, and delivery of impactful AI projects.
- Prototype proof-of-value concepts that demonstrate concrete business outcomes derived from AI capabilities on the platform.
- Advise on model selection, fine-tuning strategies, and safety frameworks while accounting for real-world operational constraints.
- Publish insights and technical narratives that strengthen the company's thought leadership in the AI space.
- Navigate ambiguous environments and shifting priorities to ensure successful project execution and stakeholder satisfaction.
Requirements
You bring an advanced degree in a quantitative discipline such as Computer Science, Physics, Mathematics, or Engineering. Equivalent experience is demonstrated through influential publications and production system implementation that prove your expertise. You have built and deployed AI systems for a minimum of eight years, with experience spanning both cloud and on-premises environments. You command deep knowledge of large language models and distributed training methodologies. You understand evaluation and alignment frameworks alongside classical machine learning methods to solve complex problems. You wield the modern AI stack in daily work, including PyTorch, vLLM, Ray, and Kubernetes. You are proficient with data platforms such as Spark, Snowflake, and Kafka to manage large-scale information flows. You direct research projects that support critical business objectives while collaborating across diverse functions. You communicate complex ideas clearly to both technical specialists and executive stakeholders to ensure alignment. You possess the ability to translate technical jargon into business language without losing essential nuance.
Nice to have
Experience presenting at industry events is valuable for visibility and thought leadership. Contributions to peer-reviewed research or technical publications are considered advantageous for demonstrating intellectual rigor.
Practical notes
You should be available for 30-60% travel with global collaboration. This role requires a commitment to interacting with international teams and clients. You must be located in the United States to comply with regional regulations and operational needs. There are no specific hours mandated, but the position demands flexibility to support global time zones. This listing directs interested candidates to the official apply page for further instructions and application submission.
Skills And Tools
Core tools include PyTorch, Kubernetes, NVIDIA, and AMD architectures. You will also utilize vLLM, Ray, Spark, Snowflake, Kafka, and Everpure platforms to deliver comprehensive solutions.
About the company
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