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Edge Ai Machine Learning Jobs in California (NOW HIRING)

Veritone

AI/Machine Learning Engineer

Irvine, CA

POSITION SUMMARY The AI/ML Engineer will participate in building, documenting, and refactoring ... machine learning workloads and production code. DISCLOSURE Our company provides equal employment ...

Klaviyo

Senior Machine Learning Engineer

Palo Alto, CA

$144K - $189K/yr

We have a big opportunity to build state-of-the-art AI and machine learning technologies at Klaviyo ... You will apply cutting-edge techniques from deep learning, recommender systems, language modeling ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

AI's strategic objectives. Key Responsibilities: * Design, build, and maintain end-to-end ML ... Ability to translate cutting-edge research from papers into clean, production-ready code ( Paper to ...

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Edge Ai Machine Learning information

What is an Edge AI Machine Learning?

An Edge AI Machine Learning job involves developing and deploying machine learning models directly on edge devices, such as IoT sensors, mobile devices, and embedded systems. This role requires expertise in optimizing AI models for low-power, low-latency environments while ensuring real-time processing. Professionals in this field work with frameworks like TensorFlow Lite, ONNX, and OpenVINO to implement AI solutions efficiently. They must also handle challenges like model compression, hardware acceleration, and data privacy.

What are the key skills and qualifications needed to thrive in the Edge AI Machine Learning position?

To thrive as an Edge AI Machine Learning professional, you need a strong background in machine learning algorithms, embedded systems, and proficiency with programming languages such as Python or C++. Familiarity with edge computing platforms (like NVIDIA Jetson, Google Coral), frameworks (TensorFlow Lite, ONNX), and certifications in AI or ML can greatly enhance your qualifications. Strong problem-solving abilities, collaboration, and effective communication skills are important for adapting solutions to diverse environments and working cross-functionally. These abilities enable the successful deployment of efficient and robust AI models directly on devices, meeting the unique challenges of real-time, resource-constrained settings.

What are some typical challenges faced in an Edge AI Machine Learning role, and how can I prepare for them?

One of the most common challenges in Edge AI Machine Learning is optimizing models to run efficiently on hardware with limited resources, while maintaining acceptable accuracy and speed. You may encounter constraints related to memory, processing power, and connectivity, which require creative engineering and a deep understanding of both machine learning and embedded systems. Collaborating closely with hardware engineers, data scientists, and software developers is typical, as solutions often span multiple technical disciplines. To prepare, staying current with advancements in model compression, quantization, and edge deployment technologies will help you tackle these challenges with confidence.

What are the most commonly searched types of Edge Ai Machine Learning jobs in California?

The most popular types of Edge Ai Machine Learning jobs in California are:

What are popular job titles related to Edge Ai Machine Learning jobs in California?

For Edge Ai Machine Learning jobs in California, the most frequently searched job titles are:

What job categories do people searching Edge Ai Machine Learning jobs in California look for?

The top searched job categories for Edge Ai Machine Learning jobs in California are:

What cities in California are hiring for Edge Ai Machine Learning jobs?

Cities in California with the most Edge Ai Machine Learning job openings:

Edge Ai Machine Learning jobs near you
Infographic showing various Edge Ai Machine Learning job openings in California as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

AI/Machine Learning Engineer

Veritone

Irvine, CA

Full-time

Medical, Life, Retirement, PTO

Re-posted 2 days ago

Job description

POSITION SUMMARYThe AI/ML Engineer will participate in building, documenting, and refactoring production-grade AI/ML pipelines, model integration layers, and scalable features that grow with business needs.WHAT YOU'LL DOProcess

  • You identify and analyze areas in existing code, model inference workflows, and data pipelines for optimization, efficiency, and latency improvements.

Team

  • You partner with product, design, data, and infrastructure teams to integrate AI/ML capabilities and intelligent services into application workflows.

  • You participate in on-call support rotation for production ML services, if necessary.

  • You actively participate in team meetings: sharing knowledge on emerging AI trends, asking questions, and challenging assumptions.

  • You actively help your team meet their commitments.

  • You are open to constructive feedback from teammates and management.

Personal

  • You continuously improve your technical skills and stay current with rapid developments in the AI/ML landscape.

  • Proven track record of writing maintainable code, including unit/integration tests, evaluation benchmarks, and readable code.

  • Expertise with learning new frameworks, algorithms, and technical stacks quickly.

  • Familiarity with our tech stack:

    • AI/ML & Data: Python, PyTorch / TensorFlow, Hugging Face, LangChain / LlamaIndex, Vector DBs (e.g., Pinecone, Qdrant, pgvector)

    • MLOps & Infrastructure: Docker, Kubernetes, MLflow / Weights & Biases, Cloud ML Platforms (AWS SageMaker, GCP Vertex AI, etc.)

    • Backend & API: Python, Go, Node.js, GraphQL, ElasticSearch, and Postgres

WHAT YOU'LL NEED

  • At least 3 years of professional experience building and deploying software systems, with direct experience integrating, fine-tuning, or operating AI/ML models in production environments.

  • Deep proficiency with Python and standard ML libraries (e.g., PyTorch, NumPy, Pandas, Scikit-learn, Hugging Face).

  • Hands-on experience with LLMs, RAG architectures, prompt engineering, or traditional ML model pipelines and inference serving.

  • Ability to design and implement robust APIs and backend microservices in Python (bonus if experienced with Go or Node.js).

  • Professional experience working with RDBMSs, NoSQL DBs, and Vector Databases.

  • Demonstrated participation in the successful deployment, monitoring, and scaling of machine learning workloads and production code.

DISCLOSURE

Our company provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics.

(Colorado & California Only*): The Annual salary listed for the position is a range of $175,000.00-$200,00.00. This base pay is for illustrative purposes only and will be determined based on skills and experience comparable to the job requirements. This position may be eligible for additional compensation and benefits including but not limited to: incentive compensation; health benefits; retirement benefits; life insurance; paid time off; parental leave and benefits; and other employee perks and benefits.

*Note: Disclosure as required by sb19-085 (8-5-20) of the minimum salary compensation for this role when being hired in Colorado & California.

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