SAN FRANCISCO

AI Engineer Recruitment

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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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Title: AI Engineer

Location: Remote, United States

Compensation: Up to $250,000 + Equity

We’re partnered with a mission-driven healthcare technology company working at the intersection of clinical data and AI. They’re reimagining how complex clinical workflows are automated, with a focus on making high-quality healthcare data more accessible, structured, and actionable. This is a company building something genuinely novel in a space where the stakes are high and the impact is real.

This is a high-impact role where you will lead AI innovation from the ground up. You won’t just be implementing models, you’ll own the full lifecycle of production AI systems, define how clinical data is extracted and structured at scale, and influence the company’s long-term AI direction. The work spans LLMs, computer vision, and mixed-modal approaches in a domain where rigor and accuracy are non-negotiable.

What You’ll Do

• Design, develop, and deploy novel AI/ML systems – with a focus on LLMs and computer vision – to recover, extract, and automate clinical data tasks across diverse data types including medical records, imaging, and clinical reports
• Build robust prototypes and transition them to scalable, near-production-ready code, applying strong software engineering fundamentals throughout
• Design and execute rigorous statistical validation and evaluation frameworks, defining performance metrics and ensuring models meet stakeholder-defined accuracy thresholds
• Own the human-in-the-loop (HITL) lifecycle, ensuring deployed models can continuously improve over time through structured feedback capture
• Partner closely with software engineering to bring proof-of-concept solutions into production, contributing to key architectural decisions along the way
• Proactively identify high-impact AI opportunities across the business and define how advanced capabilities can address them
• Champion best practices for documentation, experimentation, and code quality across the model development lifecycle – and potentially mentor others in doing the same
• Actively evaluate state-of-the-art approaches, bringing innovative ideas and methods to the team
• Apply and uphold healthcare data privacy regulations and ethical standards in all AI development work

Requirements

• MSc or PhD in computer science, engineering, applied mathematics, statistics, or a related field; BSc with equivalent demonstrated experience also considered
• 2-5+ years of relevant experience in AI/ML engineering or data science, with increasing scope and responsibility over time
• Deep hands-on Python expertise; polyglot coder comfortable across modern programming languages
• Significant experience with at least one deep learning framework (PyTorch, TensorFlow, etc.) applied to LLMs or computer vision in production contexts
• Proven knowledge of the healthcare data domain in at least one area: EHR/EMR, clinical imaging, clinical workflows, or clinical research
• Extensive experience with modern cloud compute and storage platforms (AWS, Azure, Databricks, Snowflake, etc.)
• Solid understanding of database technologies (SQL, NoSQL, etc.)
• Strong familiarity with SDLC and agile methodologies
• Ability to independently architect end-to-end solutions and clearly communicate how they deliver business value
• Excellent written and verbal communication skills – including the ability to present complex technical concepts to non-technical stakeholders

Nice to Have

• Experience with computer vision or multimodal model development
• Background in clinical research, regulated healthcare environments, or medical data pipelines
• Familiarity with EDC systems or clinical trial data infrastructure
• Experience designing or improving HITL feedback systems in production
• Exposure to AI evaluation frameworks or quality assessment tooling

If you’re interested in shaping how AI systems are built, evaluated, and deployed in high-trust environments, this is an opportunity to have direct influence on both technical direction and real-world impact at a fast-growing company.

To Apply for this Job Click Here

To Apply for this Job Click Here

Staff Applied AI Engineer | Bay Area (Hybrid) | $200k-$298k base + equity

I’m partnering with a high-growth SaaS company at the cutting edge of AI and compliance on a senior Applied AI Engineer hire.

This is not a typical “build a model and ship it” role.

This is where you define what good AI looks like – owning how systems retrieve, reason, and deliver trustworthy outputs at scale.

You’ll sit at the intersection of research and real-world impact, shaping the intelligence behind core product features.

‘ :

* Improving RAG systems – retrieval quality, chunking, embeddings, hybrid search

* Designing evaluation frameworks (metrics, golden datasets, regression detection)

* Building and tuning ranking + reranking systems (cross-encoders, LLM rerankers)

* Running experiments to validate what actually improves performance

* Debugging failure modes across retrieval, reasoning, and generation

* Prototyping agent-style workflows over complex, document-heavy data

* Exploring ML approaches beyond GenAI (ranking, classification, probabilistic models)

‘ :

* 8-10+ years in applied ML, data science, or AI research

* Strong experience in information retrieval / search relevance

* Hands-on with RAG systems and retrieval optimization

* Deep understanding of evaluation + experimentation (A/B testing, metrics)

* Python + strong problem-solving / research mindset

* Someone who can explain why systems work (or don’t) – not just build them

:

* You’ve only used LLM APIs without optimizing retrieval or evaluation

* Your experience is purely prompt engineering

* You prefer purely academic research without product impact

* You’re looking for a heavily structured, slow-moving environment

Candidates must be based in the Bay Area and open to a hybrid setup.

If you’re interested in making AI systems measurably better – not just building them, drop me a message or comment below.

Happy to share more details confidentially.

#AIJobs #MachineLearning #RAG #SearchRelevance #LLMs #Hiring #BayAreaJobs #TechJobs

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