ZipRecruiter

Log In

1

Ai Task Jobs in California (NOW HIRING)

Soulside AI

Applied AI Engineer

San Francisco, CA · On-site

$150K - $200K/yr

Design and maintain rigorous evaluation sets for high-stakes tasks like clinical reasoning and AI note generation -defining metrics, curating gold-standard data, and building automated and human-in ...

Argo AI

AI Engineer

San Francisco, CA · On-site

$210K/yr

Build and implement agentic AI systems capable of autonomous decision‑making and task execution * Develop AI‑powered automation tools to streamline workflows across operations, customer ...

YO AI Labs

AI Software Engineer - Remote

San Jose, CA · Remote

$80 - $120/hr

Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic verification systems and golden reference solutions. * Evaluate AI agents ...

HP

Software Engineer, AI Systems

Palo Alto, CA · On-site

$93K - $140K/yr

We create breakthrough solutions that make complex tasks feel effortless, teamwork more natural, and ideas more impactful-always with a human-centric mindset. By embedding AI advancements into every ...

YO AI Labs

AI Technical Trainer - Remote

Palo Alto, CA · Remote

$80 - $120/hr

Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic verification systems and golden reference solutions. * Evaluate AI agents ...

YO AI Labs

AI Technical Trainer - Remote

San Jose, CA · Remote

$80 - $120/hr

Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic verification systems and golden reference solutions. * Evaluate AI agents ...

YO AI Labs

AI Software Engineer - Remote

Los Angeles, CA · Remote

$80 - $120/hr

Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic verification systems and golden reference solutions. * Evaluate AI agents ...

YO AI Labs

AI Software Engineer - Remote

Palo Alto, CA · Remote

$80 - $120/hr

Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic verification systems and golden reference solutions. * Evaluate AI agents ...

Eloquent AI

AI Engineer, Agent

San Francisco, CA · On-site

Meet Eloquent AI At Eloquent AI, we're building the next generation of AI Operators-multimodal ... tasks with intelligent, end-to-end execution. Headquartered in San Francisco with a global ...

Eloquent AI

AI Engineer, Platform

San Francisco, CA · On-site

... tasks with intelligent, end-to-end execution. Headquartered in San Francisco with a global ... As an AI Engineer at Eloquent AI, you will be at the forefront of building and scaling AI-powered ...

F2 AI

Applied AI Engineer

San Francisco, CA · On-site

Create evaluation frameworks to measure and improve AI performance across investment research, due diligence, and portfolio monitoring tasks * Design and implement systems that maintain traceability ...

YO AI Labs

AI Technical Trainer - Remote

Los Angeles, CA · Remote

$80 - $120/hr

Design tasks involving bug fixing, feature development, refactoring, and performance optimization . * Build deterministic verification systems and golden reference solutions. * Evaluate AI agents ...

SpaceXAI

AI Tutor - Legal & Compliance

Palo Alto, CA · On-site +1

$50 - $100/hr

Collaborate with technical staff to support the training of new AI tasks and contribute to the development of innovative technologies. * Assist in designing and improving efficient annotation tools ...

previous pagenext page

Showing results 21-40

All JobsAi Task JobsAi Task Jobs in California

Ai Task information

What is an AI task?

AI tasks are specific activities or problems that artificial intelligence systems are designed to perform or solve. These can range from natural language processing, image recognition, and data analysis to autonomous decision-making and recommendation systems. AI tasks are typically defined based on the goals of an AI project and can be performed by machine learning models, algorithms, or other intelligent software. Understanding the nature of a particular AI task is crucial for choosing the right tools and methods to solve it effectively.

What are some common challenges faced by AI task specialists when working on multi-disciplinary teams?

AI Task specialists often collaborate with data scientists, software engineers, product managers, and domain experts. A common challenge is translating complex technical concepts into actionable insights for non-technical stakeholders while ensuring that the AI models align with business objectives. Balancing competing priorities, such as model accuracy versus deployment speed, and managing expectations around AI capabilities can also be demanding. Effective communication and adaptability are key to overcoming these challenges and achieving successful project outcomes.

What are the key skills and qualifications needed to thrive as an AI (Artificial Intelligence) engineer, and why are they important?

To thrive as an AI Engineer, you need a solid background in computer science, mathematics, and programming, typically supported by a relevant degree. Proficiency with machine learning frameworks (such as TensorFlow or PyTorch), programming languages (like Python), and familiarity with cloud platforms is essential, and certifications in data science or AI can be advantageous. Strong problem-solving abilities, creativity, and effective communication skills help AI Engineers design innovative solutions and explain complex concepts to diverse stakeholders. These skills ensure successful development, deployment, and integration of AI technologies in real-world applications.

What is the difference between Ai Task vs Data Annotator?

AspectAi TaskData Annotator
Required CredentialsBasic technical skills, sometimes certifications in AI or data labelingMinimal formal education, training in annotation tools often provided
Work EnvironmentRemote or on-site, often part of AI development teamsPrimarily remote, working with datasets and annotation platforms
Industry UsageAI development, machine learning projectsData preparation for AI, machine learning, and data science
Search & Comparison IntentUnderstanding roles in AI projects, job requirementsClarifying data labeling tasks and skills needed

Ai Tasks involve a range of activities related to training AI models, including data labeling, model testing, and algorithm development. Data Annotators specifically focus on labeling and annotating datasets to train machine learning models. While both roles support AI development, Ai Tasks encompass broader responsibilities, whereas Data Annotators primarily handle data preparation.

What cities in California are hiring for Ai Task jobs?

Cities in California with the most Ai Task job openings:

Ai Task jobs near you
Infographic showing various Ai Task job openings in California as of August 2026, with employment types broken down into 72% Full Time, 23% Part Time, and 5% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Applied AI Engineer

San Francisco, CA • On-site

Soulside AI
See more jobs at Soulside AIexternal

$150K - $200K/yr

Full-time

Medical, Dental, Vision

Posted 18 days ago

Key responsibilities

  • Build post-training pipelines and evaluation systems for open-source models focused on clinical tasks.

  • Fine-tune, deploy, and serve models across inference and fine-tuning platforms, making build-vs-buy decisions.

  • Design and maintain evaluation sets, define metrics, and automate assessments to ensure model quality and safety.

Job description

Applied AI Engineer
Soulside AI • US On-Site • Reports to the CTO
About Soulside
Soulside AI is the specialist AI platform for behavioral health documentation and compliance. We generate audit-ready clinical documentation across individual and group sessions, virtual and in-person care, admissions, and treatment planning-and we embed real-time chart audits and payer-aligned compliance checks into everyday workflows. The result is immediate and measurable: higher-quality charts, stronger medical necessity, and hours given back to clinicians every week.
We're backed by Counterpart Ventures, GreyMatter Capital, and One Mind, and we're a UCSF Rosenman Institute and One Mind Accelerator company. We've reached strong product-market fit and are scaling fast.
The Role
We're looking for an Applied AI Engineer to own the model layer that makes Soulside's documentation trustworthy. In behavioral health, a note isn't just text-it has to be clinically sound, defensible for medical necessity, and safe. Your job is to build the post-training pipelines and evaluation systems that get our models there, and keep them there as we scale.
This is a hands-on role for someone who lives at the intersection of applied ML and product. You'll fine-tune and adapt open-source models, stand up the infrastructure to serve them, and build the rigorous evaluation sets that tell us-objectively-whether a change made the product better or worse.
Why This Role Matters
  • Accuracy Isn't Optional: In behavioral health, a wrong or unsupported note has real clinical and financial consequences. The pipelines and evals you build are what let us ship model changes with confidence.
  • Own the Model Layer: You'll define how we post-train, evaluate, and deploy models end-to-end-not inherit someone else's stack.
  • Direct Clinical Impact: Every improvement in clinical reasoning or note quality directly reduces documentation burden and strengthens the charts clinicians and payers rely on.
What You'll Do
  • Build post-training pipelines on open-source models-supervised fine-tuning, preference optimization (DPO/RLHF), LoRA/adapters, and distillation-for domain-specific clinical tasks.
  • Fine-tune, deploy, and serve models across managed inference and fine-tuning platforms such as Fireworks AI, Baseten, and Together AI, and make pragmatic build-vs-buy calls on where each workload should run.
  • Design and maintain rigorous evaluation sets for high-stakes tasks like clinical reasoning and AI note generation-defining metrics, curating gold-standard data, and building automated and human-in-the-loop eval harnesses.
  • Turn eval results into a fast, trustworthy iteration loop: catch regressions before they ship, and quantify the impact of every model or prompt change.
  • Optimize the full LLM pipeline-prompting, retrieval, structured output validation, latency, and cost.
  • Partner with clinical experts to translate documentation and compliance requirements into model behavior and evaluation criteria.
  • Monitor models in production for quality, drift, and failure modes, and close the loop back into training data and evals.
What We're Looking For
  • 3+ years in applied ML / AI engineering, or a Master's degree in a related field, with hands-on experience taking LLM-based systems into production.
  • Practical experience with post-training / fine-tuning open-source models (e.g., Llama, Qwen, Mistral) using SFT, LoRA/PEFT, or preference-based methods.
  • Experience serving or fine-tuning models on managed platforms such as Fireworks AI, Baseten, or Together AI (or comparable inference/training infra).
  • Demonstrated ability to build evaluation frameworks for LLM tasks-you think in terms of measurable quality, not vibes.
  • Strong Python and familiarity with the modern ML tooling ecosystem (PyTorch, Hugging Face, etc.).
  • Solid grounding in prompt engineering and structured-output validation.
  • Ability to thrive in a fast-paced, remote startup and communicate clearly with technical and clinical teammates.
  • We're willing to sponsor visas, including H-1B and O-1, for the right candidate.
Bonus Points
  • Experience with healthcare, clinical NLP, or other high-stakes / regulated domains.
  • Familiarity with HIPAA and handling sensitive clinical data.
  • RAG systems, retrieval quality tuning, or long-context document workflows.
  • Experience with LLM observability, monitoring, and drift detection in production.
  • Data pipeline and labeling workflow experience for curating high-quality training and eval sets.
  • Open-source contributions in the ML/LLM ecosystem.
What We Offer
  • Salary range of $150,000-$200,000, plus equity with significant upside potential as a founding team member
  • Comprehensive health, dental, and vision insurance
  • Flexible, remote-first culture
  • Direct access to founders and influence on technical direction
  • Professional development budget and conference attendance
  • The chance to build AI that measurably improves mental health care at scale
How to Apply
Send your resume and a short note to anurag@soulside.ai. Tell us about a model or pipeline you took to production-and how you knew it was actually working.

Apply