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Ai Practitioner Jobs (NOW HIRING)

Ayo Semiconductor

AI Lead

Boston, MA · On-site

The Role We are seeking a deep AI practitioner to join as a founding team member - someone with hands-on experience working on or alongside a foundation model at scale, who understands what happens ...

kgs

Data Scientist (Remote)

Nashville, TN · Remote

Partner with the AWS AI Practitioner and AWS Solutions Architect to design and implement scalable, cloud-native data science solution architectures on AWS, leveraging Amazon SageMaker, Amazon Bedrock ...

kgs

Data Scientist (Remote)

Nashville, TN · Remote

Partner with the AWS AI Practitioner and AWS Solutions Architect to design and implement scalable, cloud-native data science solution architectures on AWS, leveraging Amazon SageMaker, Amazon Bedrock ...

Koniag, Inc.

Data Scientist (Remote)

Nashville, TN · On-site +1

Partner with the AWS AI Practitioner and AWS Solutions Architect to design and implement scalable, cloud-native data science solution architectures on AWS, leveraging Amazon SageMaker, Amazon Bedrock ...

Andrew Morgan

AI Engineer/Solution Architect

Arlington, VA · On-site

... AI Practitioner, or equivalent) • Experience in federal, regulated or compliance-driven environments • Exposure to DevOps practices, CI/CD pipelines and infrastructure as code • Familiarity ...

Qualizeal

AI Cybersecurity Consultant

Dallas, TX · On-site

AWS Certified AI Practitioner, AWS Certified Cloud Practitioner. * Cybersecurity & Governance: CompTIA Security+, CISM, CRISC, or AI Risk/Security credentials (e.g., AAIR, AAISM). Work Style & Core ...

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How much do ai practitioner jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for ai practitioner in the United States is $19.82, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $21.15 per hour, depending on experience, location, and employer.

What is an AI practitioner?

AI Practitioners are professionals who specialize in designing, developing, and implementing artificial intelligence solutions. Their work involves applying machine learning, data analysis, and advanced algorithms to solve real-world problems across various industries. They often collaborate with data scientists, engineers, and business leaders to create intelligent systems that can automate tasks, extract insights from data, and improve decision-making processes. AI Practitioners typically have expertise in programming, mathematics, and statistics, as well as experience with AI frameworks and tools.

What are the key skills and qualifications needed to thrive as an AI practitioner?

To thrive as an AI Practitioner, you need strong analytical skills, a solid grounding in mathematics and statistics, and experience with programming languages like Python, often supported by a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and certifications like TensorFlow Developer or AWS Certified Machine Learning are highly valuable. Critical thinking, problem-solving, and effective communication set outstanding practitioners apart by enabling them to translate complex models into actionable business solutions. These skills and qualities are vital for developing robust AI systems that address real-world challenges and deliver measurable impact.

What are some common challenges AI practitioners face when integrating machine learning solutions into existing business processes?

AI Practitioners often encounter challenges such as aligning machine learning models with business objectives, ensuring data quality and availability, and managing stakeholder expectations. Integrating AI solutions typically requires close collaboration with cross-functional teams, including IT, product managers, and subject matter experts, to ensure seamless deployment and adoption. Additionally, maintaining transparency and explainability of AI models can be crucial for gaining trust from non-technical stakeholders and meeting compliance requirements.

What is the difference between Ai Practitioner vs Data Scientist?

AspectAi PractitionerData Scientist
Required CredentialsCertifications in AI, machine learning, programming skillsStatistics, programming, data analysis certifications
Work EnvironmentDeveloping AI models, implementing algorithms, working with AI toolsAnalyzing data, building predictive models, interpreting data insights
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, tech firms, research institutions

While both roles involve working with data and algorithms, an Ai Practitioner primarily focuses on developing and deploying AI solutions, whereas a Data Scientist emphasizes analyzing data to extract insights and build predictive models. The roles often overlap but differ in their core focus and skill sets.

How much does an AI practitioner make?

An AI practitioner typically earns between $80,000 and $150,000 annually, depending on experience, education, and location. Professionals with advanced skills in machine learning, deep learning, and data analysis tend to earn higher salaries, especially in tech hubs or industries with high demand for AI expertise.

How to become a certified AI practitioner?

To become a certified AI practitioner, individuals typically complete relevant training programs or courses in artificial intelligence, machine learning, or data science offered by accredited institutions or online platforms. Earning industry-recognized certifications such as those from Microsoft, Google, or the Certified Artificial Intelligence Practitioner (CAIP) program can validate skills and improve job prospects.

Would an AI practitioner certificate be worth it?

An AI practitioner certificate can enhance your credentials and demonstrate knowledge of machine learning, data analysis, and AI tools. It may improve job prospects and salary potential, especially when combined with practical experience and skills in programming languages like Python or frameworks such as TensorFlow.
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Ai Practitioner jobs near you
Infographic showing various Ai Practitioner job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution, with an average salary of $41,232 per year, or $19.8 per hour.

AI Lead

Boston, MA • On-site

Ayo Semiconductor
See more jobs at Ayo Semiconductorexternal

Full-time

Medical, Dental, Vision

Re-posted 23 days ago

Job description

About Ayo

We are a venture-backed early-stage startup developing processors specialized for machine learning. The processor will provide orders or magnitude improvement in speed and power efficiency with a goal of unseating the GPU as the dominant computing platform for AI.

The Role

We are seeking a deep AI practitioner to join as a founding team member - someone with hands-on experience working on or alongside a foundation model at scale, who understands what happens under the hood when splitting jobs across thousands of GPUs, and who is excited to bring that depth to novel hardware. They have a full-stack understanding of machine learning architectures, love to optimize algorithms across disciplinary boundaries, and will deploy and train models directly on our prototype chips to help us prove out what our processor can do - no prior hardware experience required.

What You’ll Do:

  • Deploy and run trained models on prototype hardware and digital twins, producing working demonstrations on our chips.

  • Develop and adapt algorithms to train models on novel processing environments, including our prototype hardware.

  • Work with hardware engineers to define and refine processor architecture based on insights learned through model training and experimentation.

  • Maintain a deep curiosity about what makes AI systems work - and bring that curiosity to bear on how they run on new hardware.

  • Support go-to-market strategy development

What We’re Looking For:

  • PhD in machine learning, representation learning, theory of computation, or a related field - or equivalent industry experience working on foundation models at scale.

  • Experience training models at scale - distributed training across many GPUs, working with large datasets and compute.

  • Has built and trained neural networks from scratch

  • Deep knowledge of the structure and internal operation of neural networks - including how and why they behave the way they do (e.g. interpretability or explainability work is a plus).

  • Excitement about applying deep AI expertise to new and novel hardware environments - you don’t need prior experience with photonics or silicon, but you want to learn.

  • Fluent knowledge of Python

  • Fluency in PyTorch (preferred), TensorFlow, JAX, or other industry-standard ML software libraries

Why Ayo

  • You'll be a founding AI team member - shaping how we think about and deploy AI as a company.

  • We are working on a genuinely hard and interesting problem: unseating the GPU as the dominant AI compute platform.

  • Early-stage means real ownership, real impact, and meaningful equity.

  • Competitive salary. Equity commensurate with stage and seniority. Benefits package including health, dental, and vision.

  • Fully onsite in Boston - we are a collaborative, in-person team.