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Human Intelligence Task Jobs in California (NOW HIRING)

Machine Learning/Computer Vision Engineer

Sunnyvale, CA · On-site

$130K - $154K/yr

... human intelligence algorithms with applications for digital humans, health and AI. In this role ... Self-motivated with proven track record to optimally prioritize and deliver tasks on schedule.Good ...

Our vision is to enhance human intelligence by giving people perfect memory and instant access to ... with tasks. Whether you're in back-to-back meetings, brainstorming ideas, or having deep ...

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We partner ... Handle ad hoc tasks across the team - you're the person who figures things out when something pops ...

Executive Assistant

San Francisco, CA · On-site

$120K - $160K/yr

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We partner ... tasks with discretion, speed, and attention to detail. What You'll Do Executive Calendar ...

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We partner ... Scripting and automation (Python, Bash) and APIs for repetitive tasks and integrations, plus low ...

About Mercor Mercor's mission is to organize human intelligence to power the AI economy. We partner ... tasks, reconciliations, procurement workflows, variance analysis - and ship solutions that ...

Support HR administration tasks such as payroll coordination, benefits administration, and ... A self-starter who is result-oriented, resourceful, innovative, intellectually curious, and who ...

Support HR administration tasks such as payroll coordination, benefits administration, and ... A self-starter who is result-oriented, resourceful, innovative, intellectually curious, and who ...

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Human Intelligence Task information

What is the difference between Human Intelligence Task vs Data Annotation Specialist?

AspectHuman Intelligence TaskData Annotation Specialist
Required CredentialsBasic computer skills, no formal certification neededKnowledge of annotation tools, sometimes certifications in data labeling
Work EnvironmentOnline platforms, remote workRemote or in-office, often using specialized software
Employer & Industry UsageTech companies, crowdsourcing platformsAI and machine learning companies, data labeling firms
Search & Comparison IntentUnderstanding task-based work, gig economySpecialized data labeling roles, AI training

Human Intelligence Tasks (HITs) are small, simple tasks performed online, often by crowdsourced workers. Data Annotation Specialists focus on labeling data for AI training, requiring specific tools and sometimes certifications. While both roles involve online work and contribute to AI development, HITs are more general micro-tasks, whereas Data Annotation Specialists perform specialized, detailed data labeling.

What are the key skills and qualifications needed to thrive as a Human Intelligence Task worker, and why are they important?

To thrive as a Human Intelligence Task worker, you need strong attention to detail, critical thinking, and the ability to follow complex instructions, often without formal qualifications required. Familiarity with web-based platforms like Amazon Mechanical Turk or Appen, and sometimes understanding of basic data annotation tools, is beneficial. Reliability, time management, and clear written communication are standout soft skills in this role. These skills ensure high-quality, accurate task completion, which is crucial for supporting data-driven projects and research.

What are Human Intelligence Tasks (HITs)?

Human Intelligence Tasks, commonly referred to as HITs, are small, discrete jobs or assignments that require human judgment and intelligence to complete. These tasks are often posted on platforms like Amazon Mechanical Turk and can include things like identifying objects in images, transcribing audio recordings, categorizing content, or answering surveys. HITs are designed to be tasks that computers or automated systems cannot perform accurately, so they rely on human workers to provide the necessary insight and decision-making. Workers are usually paid a small amount for each completed HIT, and they can choose which tasks to accept based on their interests and qualifications.

What are some common challenges faced by individuals working on Human Intelligence Tasks (HITs) and how can they be managed?

Professionals completing Human Intelligence Tasks, such as those on platforms like Amazon Mechanical Turk, often face challenges including repetitive work, unclear task instructions, and variable compensation. To manage these, it's important to carefully review instructions before starting each HIT, use community forums to share experiences and clarify ambiguities, and select tasks from reputable requesters known for fair payment and clear expectations. Maintaining focus through regular breaks and organizing your workflow can also help mitigate fatigue and improve overall efficiency.
What job categories do people searching Human Intelligence Task jobs in California look for? The top searched job categories for Human Intelligence Task jobs in California are:
What cities in California are hiring for Human Intelligence Task jobs? Cities in California with the most Human Intelligence Task job openings:
Infographic showing various Human Intelligence Task job openings in California as of May 2026, with employment types broken down into 92% Full Time, 6% Part Time, 1% Temporary, and 1% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.
AI Engineer - Multimodal Intelligence

AI Engineer - Multimodal Intelligence

Apple

Sunnyvale, CA

$147K - $272K/yr

Full-time

Medical, Dental, Retirement

Posted 12 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers


Job description

Are you excited about the amazing potential of foundation models, LLMs, and multimodal LLMs? We are looking for individuals who thrive on collaboration and have a desire to push the boundaries of what is possible today! The VCV org is a centralized applied research and engineering organization responsible for developing real-time on-device Computer Vision and Machine Perception technologies across Apple products. In the Human Intelligence team, we balance research and product to deliver Apple quality, pioneering experiences, innovating through the full stack, and partnering with HW, SW, and ML teams to influence the sensor and silicon roadmap that brings our vision to life.
Join us in this truly exciting era of Artificial Intelligence to help deliver the next groundbreaking Apple products & experiences! We are continuously advancing the state of the art in Computer Vision and Machine Learning, touching all aspects of multimodal LLMs, from data collection, data curation to modeling, evaluation and deployment. As a member of our dynamic group, you will have the unique and rewarding opportunity to craft upcoming research directions in the field of multimodal LLMs that will inspire future Apple products.
Description
We are seeking highly motivated and skilled engineers to join our Human Intelligence team. The ideal candidates will have strong backgrounds in developing and exploring capabilities of foundation models and agentic AI systems that enable natural, proactive and personalized human interactions. You will be responsible for multimodal LLM development including training, fine-tuning, agentic AI, and reasoning systems.
In this role, you will work on cutting-edge research and engineering problems, collaborating across teams and help shape the technical direction of multimodal and agentic AI systems from research to production. You will lead and contribute to the research roadmap for multimodal foundation models, identifying key opportunities for innovation in agentic AI and reasoning capabilities. You will design and implement agentic systems, and large-scale simulation and evaluation frameworks that can transition from research prototypes to production-grade technologies.","responsibilities":"Develop, train, and fine-tune multimodal LLMs across image, video, text, and audio modalities, from data curation through deployment.
Design and build video/audio encoders, tokenizers, and generative models for multimodal understanding and generation.
Design and implement agentic AI systems that enable reliable reasoning for natural, proactive, and personalized human interactions.
Architect end-to-end ML systems that transition from research prototypes to production-grade technologies at scale.
Collaborate across HW, SW, and ML teams to influence sensor and silicon roadmaps and deliver pioneering on-device experiences.
Critically evaluate and improve ML codebases, ensuring correctness, efficiency, and maintainable engineering quality.
Contribute to the team's research direction, identify opportunities for innovation, and help shape product features.
Preferred Qualifications
PhD, or equivalent practical experience, in Computer Science, Machine Learning, Computer Vision, or a related technical field with a focus on AI, machine learning, or computer vision.
Demonstrated expertise in developing, training, and fine-tuning multimodal LLMs at scale and developing industry scale agentic products.
Proven track record of technical leadership, including architecting complex ML systems and leading projects from conception to product deployment.
Experience applying foundation models to build autonomous or semi-autonomous agents, including planning, task decomposition, and multi-step reasoning.
Strong publication record in top-tier venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, COLM, etc.
Experience with large-scale distributed training and model parallelism.
Strong communication skills and ability to present research findings to both technical and non-technical audiences.
Minimum Qualifications
Master's or equivalent practical experience, in Computer Science, Computer Vision, Machine Learning, or related technical field.
3+ years of relevant academic or industry experience in Machine Learning, Computer Vision, or Artificial Intelligence.
Experience in deep learning with demonstrated work in multimodal systems (e.g. vision, language, video, etc.).
Proficiency in Python and in a modern deep learning framework such as PyTorch or JAX.
Experience with foundation models (language or multimodal), including training, fine-tuning, and deployment.
Experience developing, training, and fine-tuning multimodal LLMs.
Strong foundations in optimization, probability, and linear algebra as applied to machine learning and computer vision.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976