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Ai Research Engineer Jobs (NOW HIRING)

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AI Research Engineer

New York, NY · On-site

$225K - $300K/yr

About the Role We're seeking an AI Research Engineer to develop and optimize our AI models and training systems. This is an exciting opportunity to apply your deep ML expertise to cutting-edge AI ...

Netic

Applied AI Research Engineer

San Francisco, CA · On-site

They are seeking an Applied AI Research Engineer to dive deep into cutting-edge research and execute targeted ML projects that deliver significant business value. Responsibilities : • Study the ...

Netic

Applied AI Research Engineer

San Francisco, CA · On-site

As an Applied AI Research Engineer, you'll dive deep into cutting-edge research, understand the business functions we put on autopilot inside-out, and execute targeted ML projects that deliver pure ...

Coram AI

AI Research Engineer - Robotics

Sunnyvale, CA · On-site

The AI Research Engineer will focus on deploying high-performance vision and multimodal models onto robotic platforms, ensuring reliability and low latency in execution. Responsibilities : • Deploy ...

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$106K

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How much do ai research engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for ai research engineer in the United States is $106,012.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,000.00 and $104,000.00 per year, depending on experience, location, and employer.

What does an AI Research Engineer do?

An AI Research Engineer designs, develops, and tests artificial intelligence models and algorithms. They work on advancing the state-of-the-art in machine learning, deep learning, and related fields, often collaborating with data scientists and software engineers. Their responsibilities typically include experimenting with new approaches, implementing prototypes, publishing research findings, and helping to integrate AI solutions into products or services. The role requires strong programming skills, a deep understanding of mathematics and statistics, and the ability to keep up with rapid advancements in AI technology.

What are the key skills and qualifications needed to thrive as an AI Research Engineer, and why are they important?

To thrive as an AI Research Engineer, you need strong expertise in mathematics, machine learning algorithms, programming (especially Python), and typically a graduate degree in computer science or a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch, experience using large datasets, and sometimes knowledge of cloud computing platforms are commonly required. Creativity, problem-solving abilities, and effective collaboration are crucial soft skills that distinguish top performers in this role. These skills and qualities are essential for developing innovative AI models, solving complex research problems, and contributing impactful solutions in a rapidly evolving field.

What are some common challenges AI Research Engineers face when transitioning research models into production environments?

AI Research Engineers often encounter challenges when moving models from research to production, such as ensuring scalability, optimizing for real-world data variability, and maintaining model performance under resource constraints. Additionally, integrating research models with existing systems and workflows can require close collaboration with software engineers and data engineers. Addressing issues like reproducibility, monitoring, and model retraining is crucial for long-term success in production settings. Proactive communication and a strong understanding of both research and engineering principles help overcome these hurdles.

What is the difference between Ai Research Engineer vs Data Scientist?

AspectAi Research EngineerData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; experience with machine learning frameworksDegree in Statistics, Computer Science, or related fields; strong analytical skills
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness analytics teams, data-driven companies, consulting firms
Employer & Industry UsageTech companies, research institutions, AI startupsFinance, healthcare, marketing, e-commerce
Common Search & Comparison IntentUnderstanding roles in AI research and developmentAnalyzing data to inform business decisions

While both roles involve working with data and algorithms, Ai Research Engineers focus on developing new AI models and advancing AI technology, often in research settings. Data Scientists analyze and interpret complex data to help organizations make strategic decisions. The roles overlap in skills like programming and machine learning, but their primary goals and work environments differ.

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Ai Research Engineer jobs near you
Adversarial AI & Research Engineer

Adversarial AI & Research Engineer

Salesforce

Los Angeles, CA • On-site

Full-time

Posted 24 days ago

Salesforce rating

7.8

Company rating: 7.8 out of 10

Based on 48 frontline employees who took The Breakroom Quiz

99th of 186 rated software companies

Job description

Job Summary:
Salesforce is the #1 AI CRM, where innovation meets action and trust. The Adversarial AI & Research Engineer will lead adversarial testing and innovate in AI attack techniques, while building security tooling and serving as a strategic partner across the company.
Responsibilities:
• Lead adversarial testing by designing, scoping, and executing red team assessments across our AI ecosystem using a risk-based prioritization approach to discover and address vulnerabilities before they can be exploited.
• Innovate in AI attack techniques by combining cutting-edge academic research with proven offensive security methods to establish new Tactics, Techniques, and Procedures, and operationalize emerging research to keep assessments aligned with the state of the art.
• Build and scale security tooling using an automation-first philosophy, driving initiatives to shift security testing left by sharing purpose-built tools with AI security stakeholders across Engineering, Research, and Ethics.
• Serve as a strategic partner across the company, providing an offensive security perspective to guide product development, support corporate governance, and contribute to policies such as Salesforce's Generative AI Security Standard.
Qualifications:
Required:
• 1+ years of experience in offensive security OR adversarial AI testing (red teaming, application security, penetration testing, vulnerability research, etc.).
• 6+ years of direct, hands-on experience testing the security of AI/ML systems, with a deep understanding of LLM vulnerabilities.
• High degree of Python proficiency for tool development, assessment automation, and data analysis.
• Proven experience leading complex technical projects and/or mentoring security teams, with exceptional ability to communicate high-stakes technical risks to both engineering and executive audiences.
Preferred:
• Advanced degree (MS or PhD) in a relevant field, or a public portfolio of security research including conference presentations, published papers, CVEs, or open-source contributions.
• Experience creating or managing large-scale datasets for security testing or machine learning training.
• Experience building automated testing frameworks or large-scale evaluation pipelines.
• Familiarity with current AI safety research and frameworks like MITRE ATLAS and the OWASP Top 10 for LLMs.
Company:
Salesforce is a cloud-based software company that provides customer relationship management software and applications. Founded in 1999, the company is headquartered in San Francisco, USA, with a team of 10001+ employees. The company is currently Late Stage.

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