DATA & AI STAFFING
SAN FRANCISCO

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AI Engineer
San Francisco, California

Remote

$200,000 – $220,000 + Equity

About the Company

This innovative health tech startup is working to improve the oncology drug development process by providing better patient data to drug developers as well as better access to clinical trials for patients. This series B startup is expending to meet demand.

About the Role

As an AI Engineer, you will design and deliver applied AI systems (LLMs/CV/multimodal) that automate clinical variable abstraction and clinical note generation-with repeatable validation, robust documentation, and HITL feedback loops. Heavy emphasis on data engineering and backend rigor to make models usable and efficient.

Role Responsibilities

• Build models and pipelines across EMR/EHR, imaging, clinical reports
• Translate ambiguous clinical requirements into measurable ML objectives
• Define metrics, design experiments, estimate error; review peer work
• Deliver validated AI components for abstraction/note generation; meaningfully reduce manual QA workload via HITL; standardize documentation/testing; establish performant data manipulation patterns (e.g., PySpark, SQL/Postgres) that speed iteration.

Key Requirements

• Python
• Pytorch or Tensorflow
• Data engineering: PySpark, SQL, Postgres, query tuning, data modeling
• Cloud data platforms (e.g., Databricks, S3/Snowflake/Azure/GCP)
• Nice to have experience in oncology/biotech/health tech

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Founding AI Engineer

San Francisco, CA (Hybrid/On‑site preferred)
Founding Team * Full‑Time
$250,000-$300,000 salary + equity

About the Role

I’m looking for a hands‑on Founding AI Engineer to build and ship the core AI systems that will drive the product forward. Your work will center on fine‑tuning large language models, designing and owning training pipelines, and deploying models that perform reliably in real‑world production environments.

This role is ideal for someone who loves building: running experiments, writing code, optimizing models, and taking features from early prototype to fully deployed. You’ll work directly with me, help define our technical direction, and make an outsized impact from day one.

What You’ll Do

• Fine‑tune and adapt leading LLMs (OpenAI, Claude, Llama, Mistral, OSS) for production use cases.

• Build hands‑on data pipelines for SFT, DPO, LoRA, RL methods, and synthetic data generation.

• Design evaluation systems to measure accuracy, reliability, grounding, and hallucination reduction.

• Develop high‑performance inference infrastructure (quantization, batching, GPU optimization).

• Own the full lifecycle of ML features: modeling → pipelines → infra → deployment.

• Rapidly experiment, iterate, and improve model performance with tight feedback loops.

• Collaborate with me on architecture decisions and product direction.

What I’m Looking For

• Strong experience fine‑tuning and deploying LLMs in production.

• Deep ML engineering skills: Python, PyTorch, transformers, distributed/accelerated training.

• Comfort handling messy, real‑world data and building robust pipelines.

• Ability to move quickly, make informed tradeoffs, and deliver production-quality systems.

• A builder’s mindset-resourceful, execution‑driven, and energized by 0→1 challenges.

⭐ Bonus Points

• Experience with agentic systems, tool‑calling, or structured reasoning workflows.

• Background in MLOps, model evaluation frameworks, or GPU-aware engineering.

• Early‑stage startup or founding-team experience.

Why Join

• Founding-level equity with meaningful ownership.

• Massive responsibility and autonomy over the AI systems at the heart of the product.

• Freedom to experiment, move fast, and push the boundaries of what LLMs can do.

San Francisco, CA (Hybrid/On‑site preferred)
Founding Team * Full‑Time
$250,000-$300,000 salary + equity

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Lead AI Engineer $250-300k + Equity – San Francisco Bay Area | Hybrid

Early-Stage Startup – Full-Time – AI Engineering

Join a fast-growing early‑stage startup building a next‑generation, AI‑native design‑to‑code platform. The team is creating a new category of design tooling where code renders directly as design, real-time AI is deeply embedded into the workflow, and designers work directly in the medium that ships to production.

We are now hiring a Lead AI Engineer as the first dedicated AI specialist on the team-owning the model layer, driving fine‑tuning strategy, and building custom SLMs that power a highly interactive, high‑performance product.

The Role

As the Lead AI Engineer, you’ll take end‑to‑end ownership of model development, optimization, deployment, and evaluation. This is a hands-on, production-focused role where you will build and maintain the AI systems at the core of the product experience.

You’ll work at the intersection of models, systems, and product-shipping production-grade AI features, shaping technical direction, and establishing best practices for evaluation and performance.

What You’ll Do

Model Fine‑Tuning & Specialization

• Lead fine‑tuning efforts across LoRA, adapters, distillation, and full fine‑tuning
• Decide when fine‑tuning, prompting, or system‑level approaches are most appropriate
• Iterate models based on real product signals and user feedback
• Balance quality, latency, reliability, and cost

Model Optimization & Performance

• Optimize inference speed, throughput, and per‑request cost
• Improve model determinism, consistency, and real-time responsiveness
• Define and maintain benchmarking, evaluation, and observability frameworks

Custom SLM Development

• Build small, fast language models tailored for design and code-generation workflows
• Identify use cases where SLMs outperform larger models
• Maintain and evolve SLMs in production environments

What You’ll Build

• Fine‑tuned models for design-to-code generation
• Custom SLMs for narrow, high‑precision workflows
• Real-time, streaming AI features inside a design environment
• Multi-step agentic systems supporting “prompt-as-cursor” and next‑in‑flow interactions

How You’ll Work

• ~80% hands‑on coding, 20% systems-level strategy
• Full lifecycle ownership: scoping → experimentation → deployment → monitoring → iteration
• Close collaboration with engineering and product leadership
• Operate within a highly senior, fast-moving engineering team
• Ideal for builders coming from AI‑native, high‑velocity environments

What We’re Looking For

Must-Have Experience

• 5+ years software engineering
• 2+ years hands‑on work with LLMs in production
• Proven fine‑tuning experience (LoRA, distillation, adapters, full fine‑tuning)
• Strong Python and TypeScript/Node.js skills
• Experience deploying custom models end‑to‑end
• Understanding of inference optimization and performance tradeoffs
• Experience with model evaluation and benchmarking

Nice-to-Haves

• ONNX Runtime
• Redis
• WebSockets
• LangChain or similar orchestration tools
• Model optimization and compression techniques
• LLM observability tooling

Ideal Background

• Experience in AI-native product startups (Seed → Series B/C)
• Work in code generation, developer tools, design tooling, or AI automation
• Strong applied experience shipping models to production at speed

How to Apply

If this role aligns with your experience and interests, please reach out with your Resume or LinkedIn profile. I would welcome a confidential conversation to explore whether it’s the right fit.

Lead AI Engineer $250-300k + Equity – San Francisco Bay Area | Hybrid

Early-Stage Startup – Full-Time – AI Engineering

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Lead AI Engineer
Location: San Francisco Bay Area | Hybrid
Salary: $250-300k + Equity

Join a well-funded, AI-native startup at the forefront of redefining how digital products are designed and shipped.

This team is building a next-generation design platform where every screen is real, production-ready code. Designers work directly in the medium that ships, not static mockups, with AI deeply embedded into the workflow to accelerate iteration while preserving precision, consistency, and control.

Backed by top-tier Bay Area investors and senior product leaders from companies including Shopify, Notion, Dropbox, Stripe, and OpenAI, the company has strong runway, a high bar for talent, and ambitious plans ahead.

They’re now hiring their first dedicated Lead AI Engineer to own the model layer and drive AI performance across the product.

The Opportunity

You’ll work directly with the CTO and founding team to define and execute the AI strategy at the model level.

This is a hands-on, production-focused AI engineering role centered on:

• Fine-tuning LLMs for real-world use cases
• Optimizing inference speed, cost, and reliability
• Designing and deploying custom Small Language Models (SLMs)
• Establishing evaluation, benchmarking, and observability standards

What You’ll Be Responsible For

Fine-Tuning & Model Strategy

• Own fine-tuning workflows (LoRA, adapters, distillation, full fine-tuning)
• Decide when to fine-tune vs optimize at the system or prompt level
• Iterate models based on production feedback
• Balance quality, latency, and cost tradeoffs

Model Optimization & Performance

• Improve inference speed and throughput
• Reduce cost per request
• Enhance reliability and output consistency
• Define model evaluation and benchmarking frameworks

Custom SLM Development

• Design and train custom SLMs for specific design-to-code workflows
• Identify when smaller models outperform larger ones
• Deploy and maintain real-time, streaming AI systems
• Support multi-step and agentic AI capabilities within the product

What They’re Looking For

• 5+ years of software engineering experience
• 2+ years building with LLMs in production environments
• Proven hands-on fine-tuning experience (LoRA, distillation, adapters, etc.)
• Experience deploying custom or specialized models
• Strong intuition around inference tradeoffs: latency, throughput, cost, reliability
• Proficiency in Python and TypeScript / Node.js

Nice to have:

• ONNX runtime or model optimization tooling
• Experience with orchestration frameworks (e.g., LangChain)
• WebSockets, Redis, or real-time streaming systems
• Background in AI-native or code-generation products
• A PhD or advanced degree is welcomed, but demonstrated production impact is the priority.

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