2

Entry Level Computer Vision Engineer Jobs in Riverside, CA

As an AI/ML Engineer on the FiFM team, you will drive research and model development for one of ... Your work will span computer vision, vision-language models (VLMs), multimodal scene understanding ...

As an AI/ML Engineer on the FiFM team, you will drive research and model development for one of ... Your work will span computer vision, vision-language models (VLMs), multimodal scene understanding ...

They are seeking a 3D Machine Learning Engineer to design, implement, and maintain advanced 3D ... Library) for classical computer vision and 3D data preprocessing. • Experience training ...

Job Title: AI/GenAI Engineer Job Location: Irvine, CA Job Type: Contract * Lead and conduct ... Design and implement machine learning deep learning natural language processing and computer vision ...

Familiarity with OpenCV and PCL (Point Cloud Library) for classical computer vision and 3D data ... Our teams span AI, software, robotics engineering, product, field deployment, and technical ...

Showing results 21-40

Entry Level Computer Vision Engineer information

See Riverside, CA salary details

$50.6K

$126.8K

$143.4K

How much do entry level computer vision engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for entry level computer vision engineer in Riverside, CA is $126,773.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,300.00 and $137,200.00 per year, depending on experience, location, and employer.

What does an entry level computer vision engineer do?

An Entry Level Computer Vision Engineer assists in developing computer systems that can interpret and process visual information from the world, such as images and videos. They typically work with machine learning algorithms, neural networks, and image processing techniques to solve problems like object detection, facial recognition, and image classification. Their work often involves data annotation, model training, testing, and optimizing algorithms under the guidance of senior engineers. Entry level engineers usually have a background in computer science or related fields and are familiar with programming languages such as Python and libraries like OpenCV and TensorFlow.

What types of projects do entry level computer vision engineers typically work on, and how much collaboration is involved?

Entry level computer vision engineers often work on tasks like annotating datasets, developing and testing algorithms for image or video analysis, and supporting the integration of computer vision models into existing applications. These projects usually require close collaboration with data scientists, senior engineers, and sometimes product managers to ensure models meet performance requirements. It's common to participate in code reviews and team meetings, fostering a supportive learning environment. As you gain experience, you'll likely take on more complex responsibilities and contribute to larger project components.

What are the key skills and qualifications needed to thrive as an entry level computer vision engineer, and why are they important?

To thrive as an Entry Level Computer Vision Engineer, you need a solid background in computer science, mathematics, and image processing, often supported by a relevant degree. Familiarity with programming languages like Python or C++, experience with deep learning frameworks (such as TensorFlow or PyTorch), and knowledge of OpenCV are typically required. Strong problem-solving abilities, attention to detail, and effective teamwork set top candidates apart. These skills and tools are essential for developing, optimizing, and implementing computer vision solutions in real-world applications.

What is the difference between Entry Level Computer Vision Engineer vs Computer Vision Analyst?

AspectEntry Level Computer Vision EngineerComputer Vision Analyst
Required CredentialsBachelor's in CS, Electrical Engineering, or related; knowledge of ML and CV frameworksBachelor's in CS, Data Science, or related; strong analytical skills
Work EnvironmentTech companies, R&D labs, startups; focus on developing algorithms and modelsData analysis teams, research firms; focus on interpreting CV data and insights
Employer & Industry UsageTech, automotive, robotics, healthcareMarket research, consulting, security, and surveillance

Entry Level Computer Vision Engineers focus on developing and implementing computer vision algorithms, often working in R&D or product teams. In contrast, Computer Vision Analysts primarily interpret and analyze CV data to generate insights. Both roles require a strong technical background, but their daily tasks and industry applications differ.

What are popular job titles related to Entry Level Computer Vision Engineer jobs in Riverside, CA?

For Entry Level Computer Vision Engineer jobs in Riverside, CA, the most frequently searched job titles are:

What job categories do people searching Entry Level Computer Vision Engineer jobs in Riverside, CA look for?

The top searched job categories for Entry Level Computer Vision Engineer jobs in Riverside, CA are:

What cities near Riverside, CA are hiring for Entry Level Computer Vision Engineer jobs?

Cities near Riverside, CA with the most Entry Level Computer Vision Engineer job openings:

Infographic showing various Entry Level Computer Vision Engineer job openings in Riverside, CA as of July 2026, with employment types broken down into 100% Full Time. Highlights an 60% In-person, and 40% Remote job distribution, with an average salary of $126,773 per year, or $60.9 per hour.

Agentic AI/ML Engineer, Multimodal

FieldAI

Irvine, CA • On-site

Full-time

Re-posted 28 days ago


Job description

FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field.
Who are We?
Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications. Learn more at https://fieldai.com.
About the Job
Our Field Foundation Model (FFM) powers a global fleet of autonomous robots that capture massive streams of multimodal data across diverse, dynamic environments every day. As part of the Insight Team our mission is to transform this raw, multimodal data into actionable insights that empower our customers and engineers to deliver value. Field-insight Foundation Model (FiFM) is at the core of how we transform multimodal data from autonomous robots into actionable insights. As an AI/ML Engineer on the FiFM team, you will drive research and model development for one of Field AI's most ambitious initiatives. Your work will span computer vision, vision-language models (VLMs), multimodal scene understanding, and long-memory video analysis and search, with a strong emphasis on agentic AI (tool use, memory, multimodal retrieval-augmented generation).This is a full-cycle ML role: you'll curate datasets, fine-tune and evaluate models, optimize inference, and deploy them into production. It's a blend of applied research and engineering, requiring creativity, rapid experimentation, and rigorous problem-solving. While FiFM is your primary focus, you'll also contribute to broader perception and insight-generation initiatives across Field AI.
What You'll Get To Do:
  • Train and fine-tune million- to billion-parameter multimodal models, with a focus on computer vision, video understanding, and vision-language integration.
  • Track state-of-the-art research, adapt novel algorithms, and integrate them into FiFM.
  • Curate datasets and develop tools to improve model interpretability.
  • Build scalable evaluation pipelines for vision and multimodal models.
  • Contribute to model observability, drift detection, and error classification.
  • Fine-tune and optimize open-source VLMs and multimodal embedding models for efficiency and robustness.
  • Build and optimize Multi-VectorRAG pipelines with vector DBs and knowledge graphs.
  • Create embedding-based memory and retrieval chains with token-efficient chunking strategies.

What You Have:
  • Master's/Ph.D. in Computer Science, AI/ML, Robotics, or equivalent industry experience.
  • 2+ years of industry experience or relevant publications in CV/ML/AI.
  • Strong expertise in computer vision, video understanding, temporal modeling, and VLMs.
  • Proficiency in Python and PyTorch with production-level coding skills.
  • Experience building pipelines for large-scale video/image datasets.
  • Familiarity with AWS or other cloud platforms for ML training and deployment.
  • Understanding of MLOps best practices (CI/CD, experiment tracking).
  • Hands-on experience fine-tuning open-source multimodal models using HuggingFace, DeepSpeed, vLLM, FSDP, LoRA/QLoRA.
  • Knowledge of precision tradeoffs (FP16, bfloat16, quantization) and multi-GPU optimization.
  • Ability to design scalable evaluation pipelines for vision/VLMs and agent performance.

The Extras That Set You Apart:
  • Experience with Agentic/RAG pipelines and knowledge graphs (LangChain, LangGraph, LlamaIndex, OpenSearch, FAISS, Pinecone).
  • Familiarity with agent operations logging and evaluation frameworks.
  • Background in optimization: token cost reduction, chunking strategies, reranking, and retrieval latency tuning.
  • Experience deploying models under quantized (int4/int8) and distributed multi-GPU inference.
  • Exposure to open-vocabulary detection, zero/few-shot learning, multimodal RAG.
  • Knowledge of temporal-spatial modeling (event/scene graphs).
  • Experience deploying AI in edge or resource-constrained environments.

Our salary range is generous and we consider each individual's background and experience when determining final compensation. Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market.
Why Join FieldAI in Irvine?
In Irvine, you will work where the robots are. Our local team builds and tests systems on real hardware with real sensors, then ships them to operate in unstructured, previously unknown environments around the world. We are solving one of robotics' hardest challenges: reliable deployment outside the lab. Our Field Foundational Models™ raise the bar for perception, planning, localization, and manipulation, with an emphasis on explainability and safety for real-world use.
You will collaborate with a world-class team that thrives on creativity, resilience, and bold thinking. We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX, along with a track record of field deployments and strong performance in DARPA challenge segments.
Be Part of the Next Robotics Revolution
We are looking for builders who want their work to leave the whiteboard and show up on robots. If you enjoy tackling tough, uncharted questions and working across disciplines, you will find your people here. Our teams span AI, software, robotics engineering, product, field deployment, and technical communication, all focused on shipping systems that perform in the real world.
Our headquarters is in Irvine, and we partner closely with teams there as well as colleagues across the US and around the world. Join us in Southern California and help define what dependable, field-ready autonomy looks like.
We value diverse perspectives and are committed to fostering an inclusive workplace. We evaluate candidates and employees based on merit, qualifications, and performance, and we do not discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected status.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.