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Senior Artificial Intelligence Testing Jobs (NOW HIRING)

$77K - $105K/yr

About the Role We are looking for a Senior AI Engineer to join our growing AI team and help build ... The Healthcare Intelligence Cloud equips every stakeholder in the patient journey to turn ...

$77K - $105K/yr

A reasonable estimate of the current salary range is $86,320 - $154,960 per year for the role of Senior Artificial Intelligence Engineer. Explore our exceptional benefits! St. Jude is an Equal ...

Ciklum is looking for a Senior AI Evaluation Engineer to join our team full-time in the US . We are a custom product engineering company that supports both multinational organizations and scaling ...

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Senior Artificial Intelligence Testing information

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$25K

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$163.5K

How much do senior artificial intelligence testing jobs pay per year?

As of Sep 11, 2026, the average yearly pay for senior artificial intelligence testing in the United States is $80,287.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,500.00 and $103,000.00 per year, depending on experience, location, and employer.

What is a senior artificial intelligence testing professional?

Senior Artificial Intelligence Testing professionals are experienced specialists responsible for designing, executing, and overseeing tests to ensure the quality, reliability, and ethical standards of AI systems. They develop test plans, create testing frameworks, and analyze AI model behaviors to identify errors, biases, or security vulnerabilities. They often collaborate with data scientists, engineers, and product managers to refine AI algorithms and ensure they perform as intended in real-world scenarios. Their role is critical in maintaining trust and safety in AI-driven products and services.

What skills and qualifications are needed to thrive as a senior artificial intelligence testing professional?

To thrive as a Senior Artificial Intelligence Testing professional, you need expertise in software testing methodologies, machine learning concepts, and proficiency in programming languages like Python, along with a degree in computer science or a related field. Familiarity with AI testing frameworks, automated testing tools (such as TensorFlow, PyTorch, Selenium), and relevant certifications (like ISTQB) is often required. Strong analytical thinking, attention to detail, and effective communication skills distinguish top performers in this role. These competencies are critical to ensuring the quality, reliability, and ethical integrity of AI systems in complex, real-world applications.

What are common challenges faced by senior artificial intelligence testing professionals, and how can they be addressed?

Senior Artificial Intelligence Testing professionals often encounter challenges such as ensuring the reliability of complex AI models, dealing with insufficient or biased data, and validating unpredictable outputs. Addressing these issues typically involves developing comprehensive test plans, employing advanced testing frameworks, and collaborating closely with data scientists and engineers. Regular communication with cross-functional teams and staying updated on the latest AI testing methodologies are also essential for overcoming these challenges and ensuring robust, ethical AI systems.

What is the difference between Senior Artificial Intelligence Testing vs Machine Learning Engineer?

AspectSenior Artificial Intelligence TestingMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, experience in AI testing toolsBachelor's or Master's in CS, strong programming skills, knowledge of ML frameworks
Work EnvironmentAI development teams, quality assurance, testing labsData science teams, software development environments, cloud platforms
Employer & Industry UsageTech companies, AI-focused firms, research institutionsTech companies, startups, research labs, AI product companies
Common Search & Comparison IntentUnderstanding testing roles in AI projectsDeveloping and deploying machine learning models

While Senior Artificial Intelligence Testing focuses on evaluating and validating AI systems for accuracy and reliability, Machine Learning Engineers design, build, and optimize machine learning models. Both roles require a strong background in computer science and AI, but their core responsibilities differ: testing emphasizes quality assurance, whereas engineering emphasizes model development and deployment.

How do I become a senior artificial intelligence testing?

To become a senior artificial intelligence testing professional, candidates typically need a strong background in computer science, machine learning, or related fields, along with experience in AI development and testing. Proficiency in programming languages like Python, knowledge of AI frameworks, and familiarity with testing tools are essential, often complemented by advanced degrees or certifications in AI or software testing. Progression usually involves gaining experience in AI projects, demonstrating leadership skills, and staying updated with emerging AI technologies and testing methodologies.

Is senior artificial intelligence testing a good career?

Senior artificial intelligence testing is a specialized role that involves evaluating AI systems for accuracy, reliability, and safety, often requiring skills in programming, data analysis, and understanding of machine learning models. It is a growing field with increasing demand as AI technologies expand across industries, offering opportunities for career advancement and specialization. The role typically requires experience, technical certifications, and knowledge of testing tools and frameworks.
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Infographic showing various Senior Artificial Intelligence Testing job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 10% Part Time, 3% Contract, and 1% Nights. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $80,287 per year, or $38.6 per hour.

Senior Artificial Intelligence Engineer

On-site

Innovaccer Inc.
IT Services • 501 - 1,000 employees

$77K - $105K/yr

Other

Medical, Dental, Vision, Life, PTO

Posted 10 days ago


Job description

About the Role

We are looking for a Senior AI Engineer to join our growing AI team and help build intelligent, production-grade AI systems that solve complex problems at scale.

In this role, you will work closely with product, engineering, and data teams to design, develop, and deploy AI-powered applications, including LLM-based solutions, AI agents, retrieval-augmented generation (RAG), and intelligent automation workflows.

The ideal candidate is hands-on, highly curious, and comfortable working across the full AI development lifecycle—from experimentation and prototyping to production deployment and optimization.

A Day in the Life
  • You take an idea from paper to prototype to production. If you have only ever done one of those three, this role will stretch you, and we are fine with that if the rest is strong.
  • You can build the model layer of a real product, not just a model. That means choosing model sizes, composing several models into a working system, and holding a product-level accuracy bar.
  • You write real code. Python fluently, PyTorch fluently, and enough systems sense to know why your training run is slow.
  • You design experiments. You state the hypothesis, run the ablation, and report the result that disagrees with you.
  • You measure things. You are suspicious of results that look good, and you build the eval before you build the model.
  • You read current research and can tell the difference between a technique that will hold up and one that will not.
  • You explain your work to people who are not AI engineers, including clinicians and operators who will tell you when your output is wrong.
What You Need
  • MS or PhD in Computer Science, Machine Learning, or a related quantitative field. Exceptional BS candidates with substantial research or open-source work will be considered.
  • Depth beyond coursework: first-author publications at NeurIPS, ICML, ICLR, ACL, EMNLP, or similar; meaningful open-source ML contributions; a research internship at an AI lab; or models you trained and shipped that people actually used.
  • You have fine-tuned an open-weight model yourself, understand the difference between parameter-efficient and full fine-tuning, and can explain why you chose one.
  • Strong Python and PyTorch. Familiarity with the current training and serving stack (HuggingFace, FSDP or DeepSpeed, vLLM or SGLang, or equivalents).
  • Some exposure to multi-GPU training, even at lab scale. You should know what a sharding strategy is and why it matters.
  • Evidence you can finish things.
  • You have post-trained models that ran in production and you know what broke.
  • You have built the model layer behind a real product feature, including fine-tuning at more than one model size and composing multiple models into a system that met a production accuracy and latency bar.
  • Hands-on multi-node training experience, tens of GPUs at minimum, on models in the tens of billions of parameters or larger.
  • You have built or substantially owned a data pipeline that fed a real training run, including the unglamorous parts: dedup, filtering, decontamination, format normalization.
  • You can scope an ambiguous problem into a plan and tell the difference between a research question and an engineering task.
  • Mentoring or setting direction for other engineers is a plus and will matter more as the team grows.

We offer competitive benefits to set you up for success in and outside of work.

Here’s What We Offer
  • Generous PTO Benefits: Enjoy PTO benefit accrual of 20 days per year.
  • Parental Leave: Experience one of the industry's best parental leave policies to spend time with your new addition.
  • Rewards & Recognition: Unlock your potential and be rewarded generously with both monetary incentives and widespread recognition for your dedication and outstanding performance. Unlock your potential and be rewarded generously with both monetary incentives and widespread recognition for your dedication and outstanding performance.
  • Insurance Benefits: We offer medical, dental, and vision benefits along with 100% company-sponsored short and long-term disability and basic life insurance. Legal aid and pet insurance options are available at a discounted rate.

Innovaccer is an equal opportunity employer. We celebrate diversity, and we are committed to fostering an inclusive and diverse workplace where all employees, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, marital status, or veteran status, feel valued and empowered.

Disclaimer

Innovaccer does not charge fees or require payment from individuals or agencies for securing employment with us. We do not guarantee job spots or engage in any financial transactions related to employment. If you encounter any posts or requests asking for payment or personal information, we strongly advise you to report them immediately to our HR department at px@innovaccer.com. Additionally, please exercise caution and verify the authenticity of any requests before disclosing personal and confidential information, including bank account details.

About Innovaccer

Innovaccer activates the flow of healthcare data, empowering providers, payers, and government organizations to deliver intelligent and connected experiences that advance health outcomes. The Healthcare Intelligence Cloud equips every stakeholder in the patient journey to turn fragmented data into proactive, coordinated actions that elevate the quality of care and drive operational performance. Leading healthcare organizations like CommonSpirit Health, Atlantic Health, and Banner Health trust Innovaccer to integrate a system of intelligence into their existing infrastructure— extending the human touch in healthcare. For more information, visit www.innovaccer.com.

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