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Ai Machine Learning Engineer Jobs (NOW HIRING)

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

BeeGenius is building the future of work, and they are seeking an AI/Machine Learning Engineer to join their team. In this role, you will be responsible for developing and implementing machine ...

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

Bee Genius is building the future of work and is seeking an AI/Machine Learning Engineer to join their team. The role involves developing and implementing machine learning models and algorithms to ...

Schneider

AI & Machine Learning Engineer

Green Bay, WI · On-site

$94K - $129K/yr

AI & Machine Learning Engineer Work model:On-Site Location:Green Bay, WI, USA Shift:First shift Job level:Individual Contributor Schedule:Full time; Mon-Fri 1st Shift Apply now Get job alerts Job ...

CyberMedia Technologies

AI / Machine Learning Engineer

$117K - $140K/yr

We are seeking to hire a AI/Machine Learning Engineer to our team! Role Overview: As an AI/ML Engineer for CTEC, you will develop Agentic AI systems designed to automate and optimize health benefits ...

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All JobsAi Machine Learning Engineer Jobs

Ai Machine Learning Engineer information

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$31.5K

$128.8K

$193.5K

How much do ai machine learning engineer jobs pay per year?

As of Aug 3, 2026, the average yearly pay for ai machine learning engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI machine learning engineer?

To thrive as an AI Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python or R), and a relevant degree such as computer science or engineering. Familiarity with frameworks like TensorFlow, PyTorch, and scikit-learn, as well as experience with cloud platforms and data processing tools, is highly valued, along with certifications in AI or machine learning. Critical thinking, problem-solving, and effective communication are essential soft skills for collaborating with teams and translating business needs into technical solutions. These competencies are crucial for developing accurate, scalable AI models that deliver real-world value and drive innovation.

What are some common challenges that AI machine learning engineers face when deploying models to production environments?

AI Machine Learning Engineers often encounter challenges such as ensuring model scalability, managing data pipeline reliability, and handling model drift once solutions are live. They also need to collaborate closely with DevOps and software engineering teams to integrate models seamlessly into existing systems, while maintaining performance and security. Addressing these challenges requires a strong understanding of both machine learning principles and software deployment best practices.

What is an AI machine learning engineer?

An AI Machine Learning Engineer is a professional who designs, builds, and deploys artificial intelligence and machine learning models to solve real-world problems. They work with large datasets, select appropriate algorithms, and optimize models for accuracy and efficiency. Their role often involves both software engineering and data science skills, and they collaborate with other teams to integrate these models into products or services. AI Machine Learning Engineers are in high demand across industries such as technology, healthcare, finance, and more.

What is the difference between Ai Machine Learning Engineer vs Data Scientist?

AspectAi Machine Learning EngineerData Scientist
CredentialsDegree in CS, AI, or related fields; certifications in ML frameworksDegree in CS, Statistics, or related fields; certifications in data analysis
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, where deploying ML models is keyResearch, business intelligence, analytics across industries

While both roles involve working with data and machine learning, Ai Machine Learning Engineers focus on building and deploying scalable ML models in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core focus and responsibilities.

More about Ai Machine Learning Engineer jobs
What cities are hiring for Ai Machine Learning Engineer jobs? Cities with the most Ai Machine Learning Engineer job openings:
What states have the most Ai Machine Learning Engineer jobs? States with the most job openings for Ai Machine Learning Engineer jobs include:
What job categories do people searching Ai Machine Learning Engineer jobs look for? The top searched job categories for Ai Machine Learning Engineer jobs are:
Ai Machine Learning Engineer jobs near you
Infographic showing various Ai Machine Learning Engineer job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

AI/Machine Learning Engineer

BeeGenius

Sunnyvale, CA • On-site

Full-time

Re-posted 9 days ago

Job description

Job Summary:
BeeGenius is building the future of work, and they are seeking an AI/Machine Learning Engineer to join their team. In this role, you will be responsible for developing and implementing machine learning models and algorithms to solve complex business problems.
Responsibilities:
• Design and develop machine learning models and algorithms
• Train and evaluate models using large datasets
• Optimize and fine-tune models for performance and accuracy
• Collaborate with data scientists and software engineers to integrate models into production systems
• Stay updated with the latest advancements in AI and machine learning
• Ensure the ethical use of AI technologies
Qualifications:
Required:
• Master's or Ph.D. in Computer Science, Data Science, or a related field
• Strong programming skills in Python or R
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch)
• Knowledge of statistical analysis and data visualization techniques
• Understanding of deep learning architectures and algorithms
• Excellent problem-solving and critical-thinking skills
Company:
We are a leading technology, digital, and outsourcing services company. Founded in 2014, the company is headquartered in , , with a team of 2-10 employees. The company is currently Early Stage.

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