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AI Fund · 2 hours ago

Lead AI Engineer

San Francisco, CA

Full-time

Hybrid

Senior Level, Lead/Staff

$180K/yr - $225K/yr

5+ years exp

AI Fund is a mission-driven startup reinventing the way people find peace and inspiration through digital experiences. The Lead AI Engineer will architect and evolve the cognitive engine of the platform, focusing on model tuning, inference optimization, and intelligent orchestration.

Artificial Intelligence (AI)

Growth Opportunities

H1B Sponsor Likely

Responsibilities

Lead fine-tuning of foundational models using efficient training techniques and custom datasets

Design and implement model orchestration logic that determines when to retrieve, route, generate, or escalate across different conversational contexts

Build and iterate on eval frameworks for long-form, multi-turn interactions - prioritizing emotional coherence and user outcomes over token accuracy

Stay on top of rapid developments in LLMs, fine-tuning frameworks, and inference efficiency, translating that knowledge into action

Champion best practices for scaling training workflows, experimenting safely, and continuously learning from real-world feedback

Design, iterate, and evaluate prompt strategies for complex multi-turn interactions using frameworks like DSPy

Build prompt libraries and A/B test variants to optimize for safety, clarity, and on-brand responsiveness

Leverage prompt engineering as a short-term strategy where fine-tuning is not yet appropriate, with a clear view on trade-off

Evaluate and integrate modular orchestration strategies (e.g., LangGraph, LlamaIndex, Letta, PydanticAI), forming a perspective on their relevance and scalability

Design systems that can switch between reflection, coaching, or directive states based on context, using either routing logic or learned behavior

Collaborate with the product team to define how tools, memory, and reasoning modules interact without overcomplicating the user experience

Own parameter-efficient fine-tuning pipelines (e.g., LoRA, QLoRA) to adapt foundational models to brand-specific voice, tone, and emotional range

Curate high-quality datasets and design eval metrics tailored to coherence, empathy, and state consistency across sessions

Explore model compression, quantization, and inference optimization for low-latency voice and mobile interactions

Design lightweight experiments to validate technical approaches and measure outcomes beyond accuracy (e.g., trust, emotional congruence)

Partner with domain experts to implement human-in-the-loop annotation systems where automation falls short

Ship prototypes and production features rapidly, with a build-learn-refine approach

Qualification

Fine-tuning large language modelsModel optimization strategiesPythonModel training workflowsScalable data pipelinesPrompt engineeringCommunicatorExperimental mindsetCollaborative mindset

Required

5+ years in AI/ML engineering, with at least 2 years of hands-on fine-tuning large language models

Demonstrated expertise in applied AI within early-stage startups or product teams - you can speak to the lived experience of leading teams and projects through rapid growth and production

Strong understanding of the trade-offs between fine-tuning, tool invocation, prompt orchestration, and hybrid approaches

Proficiency with model training workflows, scalable data pipelines, and LLM evaluation techniques

Practical experience with low-latency inference environments and model optimization strategies (quantization, compression, routing logic)

Comfortable in Python and modern ML tooling; experienced deploying models to production environments

Ability to translate product or psychological intent into model architecture or training strategy

Prior work in behavioral health, mental wellness or adjacent domains, demonstrating sensitivity to emotionally resonant interactions

Experimental mindset with a bias toward measurable learning and iterative improvement

Strong communicator who can explain the “why” behind the “how” to technical and non-technical partners alike

Demonstrated curiosity for emerging methods and a track record of staying current on deep learning advancements

Team-first engineer who values listening as much as leading, who can mentor engineers in best practices while staying open to feedback

Comfortable with challenging ideas while seeking the best solution, not credit

Motivated by impact and aligned to our mission of building AI that helps people

Adaptable to small-team dynamics and comfortable operating as the technical leader in a flat team structure, collaborating closely with product & engineering teams

Preferred

Experience at AI-first companies

Experience building products in the behavioral health or digital wellness space

Knowledge of conversational state management, memory systems, or emotional alignment in LLMs

Exposure to orchestrated AI frameworks or modular agentic architectures

Benefits

Medical, dental, and vision for you and your family

Flexible PTO and mental wellness support

Annual budget for courses, conferences, or certifications

One-time home office setup stipend

Company-sponsored life and disability insurance + 401(k)

Company

AI Fund

AI Fund is a VC firm made up of AI pioneers, operators, entrepreneurs, and investors, supported by LPs such as NEA, Sequoia and Greylock.

Founded in 2017

Palo Alto, California, USA

11-50 employees

https://aifund.ai/

H1B Sponsorship

AI Fund has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

Distribution of Different Job Fields Receiving Sponsorship

Represents job field similar to this job

Trends of Total Sponsorships

2023 (2)

2020 (1)