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Meta Learning Jobs (NOW HIRING)

Nace AI

Research Engineer

Palo Alto, CA · On-site

Research expertise in LLM reasoning, hypernetworks, multi-task learning, meta-learning, designing novel LLM adaptation methods, Online Continual Learning

Nace AI

Machine Learning Engineer

Palo Alto, CA

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 ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

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 ...

Quantum Machines

Machine Learning Engineer

Chicago, IL · On-site

... meta-learning- advantage Company : Quantum Machines is a leading provider of quantum control solutions, powering quantum-classical integration at scale with Hybrid Control. Founded in 2018, the ...

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How much do meta learning jobs pay per hour?

As of Jun 15, 2026, the average hourly pay for meta learning in the United States is $37.34, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $49.76 per hour, depending on experience, location, and employer.

What is meta learning?

Meta learning, often referred to as 'learning to learn,' is a subfield of machine learning where algorithms are designed to improve their learning process based on previous experiences. Instead of simply learning a specific task, meta learning models aim to generalize from past tasks to solve new, unseen tasks more efficiently. This approach is particularly useful in situations with limited data, as the model leverages knowledge gained from previous tasks to quickly adapt. Meta learning is widely applied in areas like few-shot learning, optimization, and reinforcement learning.

Is ML a high paying job?

Meta Learning is a specialized area within machine learning that often offers competitive salaries, especially for roles requiring advanced skills in algorithms, programming, and data analysis. Salaries vary based on experience, location, and industry, but machine learning professionals generally earn above average wages compared to many other tech roles.

Which 3 jobs will survive AI?

Meta Learning as a field focuses on developing algorithms that improve with experience, and jobs that require complex problem-solving, creativity, and emotional intelligence are more likely to survive AI automation. Roles such as data scientists, AI specialists, and human-centered designers are expected to remain in demand due to their reliance on advanced skills and adaptability. Continuous learning and expertise in AI tools can also enhance job security in these areas.

What are some common challenges faced by professionals working in meta learning, and how can they be addressed?

Professionals in meta learning often encounter challenges such as limited high-quality meta-data, ensuring model generalizability across tasks, and balancing computational efficiency with performance. Addressing these issues typically involves collaborating closely with data scientists and machine learning engineers to curate diverse datasets, experimenting with various meta-learning algorithms, and optimizing model architectures for scalability. Staying updated with the latest research and engaging in cross-functional discussions can help overcome these challenges and drive innovation within the team.

Is it hard to get hired by Meta?

Getting hired for a Meta role related to machine learning or AI, such as in meta learning, can be competitive due to high standards for technical skills, experience, and education. Candidates typically need strong programming abilities, knowledge of machine learning frameworks, and relevant project experience to succeed in the hiring process.

What job makes $10,000 a month without a degree?

Meta learning is a skill that can lead to high-paying roles such as freelance consulting, online coaching, or specialized content creation, which can earn $10,000 or more monthly. Success in these areas typically requires expertise, strong self-marketing, and building a client base or audience, rather than formal education credentials.

What is the difference between Meta Learning vs Data Scientist?

AspectMeta LearningData Scientist
Required CredentialsAdvanced degrees in AI, machine learning, or related fieldsBachelor's or master's in data science, statistics, or related fields
Work EnvironmentResearch labs, AI startups, tech companies focusing on machine learning modelsBusiness environments, analytics teams, tech companies analyzing data
Industry UsagePrimarily in AI research, machine learning model developmentAcross industries like finance, healthcare, marketing for data analysis

Meta Learning focuses on developing algorithms that learn how to learn, often used in AI research. Data Scientists analyze data to extract insights and build predictive models. While both roles involve machine learning, Meta Learning is more research-oriented, whereas Data Scientists apply data techniques to solve business problems.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of algorithms and statistics, and a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, cloud platforms, and data processing tools is essential, along with relevant certifications such as Google Professional ML Engineer. Strong problem-solving abilities, communication, and adaptability help you work effectively in teams and translate business needs into technical solutions. These skills are critical for developing, deploying, and maintaining robust machine learning models that address real-world problems.
More about Meta Learning jobs
What states have the most Meta Learning jobs? States with the most job openings for Meta Learning jobs include:
What job categories do people searching Meta Learning jobs look for? The top searched job categories for Meta Learning jobs are:
Meta Learning jobs near you

Research Engineer

Nace AI

Palo Alto, CA • On-site

Full-time

Posted 27 days ago

Job description

Role Description
This role is on-site in Palo Alto, CA.
Nace AI is building the next generation of enterprise intelligence - advanced long-horizon reasoning models and autonomous agents designed to execute complex financial workflows with precision. Our flagship product, Agentic Accounting, enables financial audit, billing audit, and revenue leakage detection with speed and accuracy that traditional systems cannot match.
We are at a pivotal stage in our growth. While we've already achieved sufficient funding, our ambitions are much larger. Our goal is to become the foundational AI platform for intelligent financial operations across the enterprise.
The work we are doing has meaningful impact across industries, and every hire at Nace AI plays a critical role in shaping the company's trajectory. This is a unique opportunity to join a high conviction AI company at an early stage and directly influence its growth.
If building a world-class AI team from the ground up excites you, we'd love to talk.
Minimum Qualifications
  • Direct experience working with Large Language Models (LLMs) or Vision-Language Models (VLMs) in research or production settings
  • Strong research background in Natural Language Processing, Machine Learning, or related disciplines with focus on language modeling
  • Proven track record in solving complex problems in language understanding, generation, or multimodal AI using rigorous quantitative methodologies
  • Demonstrated ability to clearly communicate research findings to diverse technical audiences
  • Proficient programming skills in Python and deep learning frameworks (PyTorch, JAX, or TensorFlow), with experience in distributed training and model optimization

Preferred Qualifications
  • PhD in Computer Science, Computational Linguistics, or closely related field with focus on language models and adaptive learning systems
  • Proven research and engineering experience with LLMs/VLMs, particularly in meta-learning or parameter-efficient adaptation, as evidenced by grants, fellowships, patents, internships, or contributions to open-source projects
  • First authored publications on language models, meta-learning, hypernetworks, or adaptive AI in recognized peer-reviewed conferences (ACL, EMNLP, NeurIPS, ICML, ICLR) or journals
  • Kaggle experience is a plus.

Preferred Technical Experience
  • Research expertise in LLM reasoning, hypernetworks, multi-task learning, meta-learning, designing novel LLM adaptation methods, Online Continual Learning

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