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Meta Machine Learning Jobs in California (NOW HIRING)

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

Nace AI is a company focused on machine learning solutions, and they are seeking a Machine Learning ... implement meta-learning methods to enhance model generalization and efficiency. • Improve ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine ... Fine-tune large language models (LLMs) and implement meta-learning methods to enhance model ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

They are seeking a Machine Learning Engineer to translate research into scalable solutions ... implement meta-learning methods to enhance model generalization and efficiency. • Improve ...

Meta

Computer Vision Engineer

Burlingame, CA

$183K/yr

Meta Reality Labs is seeking a Machine Learning Engineer to drive the productization of gesture recognition models for our AR/VR devices. This role bridges research and production--you'll take ML ...

Meta

Research Engineer, Computer Vision

Sunnyvale, CA

$183K/yr

Apply relevant AI and machine learning techniques to build intelligent rich perception systems that improve Meta's products and experiences * Assist in goal setting related to project impact, AI ...

Meta

AI Research Manager

Menlo Park, CA · On-site +1

$219K/yr

In this role, you will drive the strategy, execution, and culture of AI research teams working on large-scale machine learning systems, foundation models, and applied AI innovations that power Meta ...

Meta

Computer Vision Engineer

Sunnyvale, CA · On-site

$183K/yr

Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations ...

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Meta Machine Learning information

What is a meta machine learning?

A Meta Machine Learning job typically involves developing and optimizing machine learning models at scale, often within Meta (formerly Facebook). These roles focus on improving AI algorithms, researching new techniques, and deploying models across products like Facebook, Instagram, and WhatsApp. Engineers and researchers in this field work with large datasets, deep learning frameworks, and distributed computing. The role requires expertise in machine learning, software engineering, and data science to enhance Meta's AI-driven capabilities.

What are the key skills and qualifications needed to thrive in meta machine learning?

To thrive in Meta Machine Learning, you need a deep understanding of advanced machine learning algorithms, meta-learning techniques, data science, and a degree in computer science or a related field. Experience with tools like Python, TensorFlow, PyTorch, as well as familiarity with cloud computing platforms and relevant certifications (such as AWS Certified Machine Learning Specialty) are highly valuable. Strong analytical thinking, creative problem-solving, and collaborative communication are essential soft skills for excelling in this area. These competencies enable practitioners to develop and optimize meta-learning models, drive innovation, and efficiently work in cross-functional tech teams.

What are some of the main challenges faced in a meta machine learning role?

Professionals in Meta Machine Learning often encounter challenges such as working with limited labeled data, creating models that generalize well across diverse tasks, and optimizing algorithms to learn efficiently from smaller datasets. The fast-paced nature of research and the need to stay updated with cutting-edge advancements in the field can also require continual learning and adaptation. Collaboration with other data scientists, engineers, and domain experts is common, making teamwork and clear communication critical for successful project delivery. Overcoming these challenges not only sharpens technical skills but also offers rewarding opportunities for innovation and career growth in this evolving field.

What are the most commonly searched types of Meta Machine Learning jobs in California? The most popular types of Meta Machine Learning jobs in California are:
What are popular job titles related to Meta Machine Learning jobs in California? For Meta Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Meta Machine Learning jobs in California look for? The top searched job categories for Meta Machine Learning jobs in California are:
Meta Machine Learning jobs near you
Infographic showing various Meta Machine Learning job openings in California as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Machine Learning Engineer

Nace AI

Palo Alto, CA • On-site

Full-time

Re-posted 29 days ago

Job description

Job Summary:
Nace AI is a company focused on machine learning solutions, and they are seeking a Machine Learning Engineer to translate cutting-edge research into scalable, production-ready solutions. The role involves designing and maintaining ML systems, collaborating with cross-functional teams, and enhancing existing models with the latest advancements in machine learning.
Responsibilities:
• Design, build, and maintain end-to-end ML systems, including synthetic data pipelines, model training, debugging, and performance evaluation.
• Fine-tune large language models (LLMs) and implement meta-learning methods to enhance model generalization and efficiency.
• Improve existing Nace.AI models by incorporating advancements from recent ML research.
Qualifications:
Required:
• Hands-on experience training and fine-tuning large language models (LLMs) and vision-language models (VLMs), including practical work with pre-training, instruction tuning, and alignment techniques (GRPO,RLHF/DPO/PPO).
• Hands-on Experience with Deep Learning Models, especially Transformers.
• Ability to translate cutting-edge research from papers into clean, production-ready code (Paper to Code).
• Proven experience scaling inference infrastructure for LLMs/VLMs, including expertise in model serving frameworks like vLLM, TGI.
• Proficient in Python with a strong track record of building substantial projects.
• Solid foundation in computer science fundamentals (data structures, algorithms, design patterns).
• BS degree in CS or related technical field.
• Solid Experience with ML frameworks and libraries (PyTorch, TensorFlow).
• Self-starter comfortable working in a fast-paced, dynamic environment.
Preferred:
• MS/PhD in CS or related technical field.
• Familiarity with data processing stacks such as Spark and Airflow.
• Experience with multi-node GPU training.
• Contributor to open-source ML projects.
• Deep knowledge in Linear Programming.
• Experience with advanced NLP and Multimodal post-training experience (e.g., model distillation, quantization, deployment optimization).
• Experienced in inference time optimization, deep understanding of LLM serving optimizations for LLMs/VLMs.
• Hands on experience with quantization techniques (AWQ, GPTQ, FP8/GGUF).
Company:
Enterprise AI product & research company, building long-horizon reasoning models and agents. Founded in 2024, the company is headquartered in Palo Alto, USA, with a team of 11-50 employees. The company is currently Early Stage.

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