Applied AI Engineer

Pantomath

. Build and ship AI agents that solve complex enterprise problems and deliver customer value .

Posted 10/5/2026full-timeCalifornia • United StatesMid-LevelSenior💰 $150,000 - $230,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and shipping AI systems, with a strong focus on model adaptation techniques, data quality, and experimental design. Proficient in collaborating with cross-functional teams to translate research into scalable product capabilities.

Highest-signal resume keywords

AI Systems DevelopmentPost-Training Tools (PyTorch, Hugging Face Transformers)Supervised Fine-TuningModel Evaluation and AdaptationSoftware Engineering (Python, TypeScript)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Systems DevelopmentModel Adaptation TechniquesSupervised Fine-TuningParameter-Efficient AdaptationModel EvaluationData Quality AssessmentExperimental DesignDistributed SystemsSoftware EngineeringPython

Soft Skills

Clear CommunicationTechnical JudgmentCollaborative Approach

Tools & Technologies

PyTorchHugging Face TransformersTRLPEFTFSDPDeepSpeedVLLM

Industry Keywords

AI AgentsEnterprise ProblemsData PipelinesSynthetic Data GenerationHuman Feedback Systems

Tech Stack

Tools & technologies

Distributed SystemsPythonPyTorchTypeScript

About the role

Key responsibilities & impact

Build and ship AI agents that solve complex enterprise problems and deliver customer value
Explore fine-tuning, post-training, and other model adaptation techniques for enterprise tasks
Design experiments and evaluations; build datasets, benchmarks, and feedback loops
Develop services, integrations, and infrastructure supporting reliable agent execution at scale
Turn promising research experiments into product capabilities, including implementation, deployment, and ongoing improvement
Improve production performance through tradeoffs across quality, reliability, latency, cost, and security
Partner with engineering, product, and customer-facing teams to identify valuable problems and effective approaches

Requirements

What you’ll need

Experience building and shipping AI systems, with substantial hands-on contributions to code, experimentation, and production engineering
Hands-on experience with post-training tools such as PyTorch, Hugging Face Transformers, TRL, and PEFT
Experience with supervised fine-tuning, parameter-efficient adaptation such as LoRA, and preference optimization or reinforcement learning
Practical experience with LLMs, agent systems, and model evaluation
Experience adapting or training models, including understanding of data quality, experimental design, and generalization
Exposure to training and evaluation data pipelines, synthetic data generation, or human feedback systems
Working knowledge of agent orchestration, tool use, retrieval, or inference optimization
Comfort working with enterprise data platforms, distributed systems, or production AI infrastructure
Familiarity with distributed GPU training and efficient inference using FSDP, DeepSpeed, or vLLM
Familiarity with reproducible experimentation and model evaluation
Strong software engineering fundamentals and proficiency in Python, TypeScript, or comparable languages
Ability to read research, reproduce useful results, and assess real-world applicability
Comfort owning ambiguous problems and moving between research exploration and product delivery
Clear communication, technical judgment, and collaborative approach

Benefits

Comp & perks

Exempt classification; not eligible for overtime compensation
Reasonable accommodations during the application/interview process and throughout employment
Equal Opportunity Employer