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Machine Learning Ai Jobs (NOW HIRING)

Element Solutions

Machine Learning/AI Engineer

The Machine Learning/AI Engineer will work across the full model lifecycle-from data preparation and feature engineering to model training, deployment, and monitoring-in a regulated government ...

Rivian

Machine Learning/AI Engineer

Palo Alto, CA

$139K - $155K/yr

... aware AI. Hands-on experience with quantized model deployment, ML design stacks, and code ... Experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and their low-level IRs or ...

Rivian

Machine Learning/AI Engineer

Palo Alto, CA · On-site

$139K - $155K/yr

Role Summary We are looking for a Research Scientist with deep expertise in quantized deep learning ... aware AI. • Hands-on experience with quantized model deployment, ML design stacks, and code ...

Anytime AI

Be Seen First

Machine Learning Engineer

OR · Remote

$100K - $200K/yr

About Anytime AI At Anytime AI, we are building the Premier AI Legal Assistant for Plaintiff ... Position Overview As a Machine Learning Engineer, you will be instrumental in crafting and refining ...

Rivian

Machine Learning/AI Engineer

Palo Alto, CA

$139K - $155K/yr

Experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and their low-level IRs or ... aware AI. Hands-on experience with quantized model deployment, ML design stacks, and code ...

Aivra Health LLC

$28 - $45/hr

H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position Overview We are seeking a highly motivated Machine Learning Engineer Intern to join our AI/ML team. This role is ideal for ...

Aivra Health LLC

$28 - $45/hr

H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position Overview We are seeking a highly motivated Machine Learning Engineer Intern to join our AI/ML team. This role is ideal for ...

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$25.5K

$42.6K

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How much do machine learning ai jobs pay per year?

As of May 30, 2026, the average yearly pay for machine learning ai in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Machine Learning AI Engineer, you need a strong background in mathematics, statistics, programming (typically Python), and a relevant degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow and PyTorch, as well as cloud platforms and data processing tools, is essential, and certifications in these areas can be advantageous. Strong problem-solving, communication, and collaboration skills help you effectively translate business needs into technical solutions and work well within multidisciplinary teams. These skills ensure you can develop robust AI models that address real-world challenges and deliver meaningful business impact.

What are some common challenges faced when collaborating with cross-functional teams as a Machine Learning AI professional?

As a Machine Learning AI professional, you’ll often collaborate with data engineers, software developers, and product managers. A common challenge is bridging the gap between complex AI models and practical business requirements, ensuring your solutions are both technically sound and aligned with user needs. Effective communication is key, as you’ll need to explain technical concepts to non-technical stakeholders and adapt your models based on feedback. Building trust and fostering a collaborative environment will help ensure successful project outcomes and foster continual learning.

What is a Machine Learning AI specialist?

A Machine Learning AI specialist is a professional who develops algorithms and models that enable computers to learn from and make predictions or decisions based on data. They work with large datasets, train and evaluate machine learning models, and often collaborate with software engineers and data scientists to integrate AI solutions into products and services. Their work is crucial in fields like natural language processing, computer vision, and predictive analytics, helping organizations automate tasks, gain insights, and improve efficiency.

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

AspectMachine Learning AiData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; experience with programming and algorithmsDegree in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentDeveloping algorithms, training models, deploying AI systemsAnalyzing data, creating reports, interpreting results
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, marketing, tech firms

Machine Learning Ai focuses on developing and deploying AI algorithms and models, while Data Scientists analyze and interpret data to inform business decisions. Both roles often collaborate but have distinct focuses within the data and AI ecosystem.

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What states have the most Machine Learning Ai jobs? States with the most job openings for Machine Learning Ai jobs include:
What job categories do people searching Machine Learning Ai jobs look for? The top searched job categories for Machine Learning Ai jobs are:
Machine Learning Ai jobs near you
Machine Learning/AI Engineer

Machine Learning/AI Engineer

Element Solutions

Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 29 days ago

Job description

Who is Element?
We serve as a partner at the intersection of innovation and our clients' needs, efficiently crafting meaningful user experiences for government and commercial customers. By breaking down complex problems to their fundamental elements, we create modern digital solutions that drive efficiencies, maximize taxpayer dollars, and deliver essential outcomes that serve the people.
Why Work at Element?
Make an impact that resonates-join our vibrant team and discover how you can improve lives through digital transformation. Our talented professionals bring unparalleled energy engagement, setting a higher standard for impactful work. Come be a part of our team and shape a better future.
Position Summary:
We are seeking a highly skilled and motivated Machine Learning / AI Engineer to support a federal government program focused on designing, developing, and deploying production-grade artificial intelligence and machine learning solutions. The role will focus on building scalable, secure, and high-performing AI models that support mission-critical decision-making and operational efficiency.
The Machine Learning/AI Engineer will work across the full model lifecycle-from data preparation and feature engineering to model training, deployment, and monitoring-in a regulated government environment.
Key Responsibilities
  • Develop and deploy at least three (3) production-grade AI/ML models, including use cases such as predictive maintenance, anomaly detection, classification, forecasting, or optimization.
  • Design, build, and maintain end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.
  • Apply deep expertise in PyTorch and/or TensorFlow to develop and fine-tune advanced machine learning and deep learning models.
  • Implement and support scalable model serving architectures, ensuring high availability, low latency, and secure inference in production environments.
  • Collaborate with data engineers to access, transform, and prepare large-scale datasets for model training and inference.
  • Partner with product owners, analysts, and stakeholders to translate business requirements into machine learning solutions.
  • Monitor model performance in production, including drift detection, accuracy tracking, and retraining strategies.
  • Ensure compliance with federal security, privacy, and governance standards in all AI/ML implementations.
  • Participate in Agile development cycles, including sprint planning, design reviews, and technical demonstrations.
  • Document model architectures, training methodologies, and deployment processes for maintainability and auditability.

Minimum Requirements
  • Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Mathematics, or related field (or equivalent experience).
  • 3+ years of experience in machine learning, data science, or AI engineering roles.
  • Proven experience delivering production-grade machine learning models in real-world environments.
  • Expert proficiency in Python and ML frameworks (scikit-learn, TensorFlow, PyTorch).
  • Advanced SQL development experience, including complex queries, performance tuning, and data transformation logic.
  • Experience leveraging Large Language Models (LLMs) in development.
  • Understanding of core concepts such as context windows, prompt design, and input/output structures, with the ability to apply AI tools effectively in building and enhancing solutions.
  • Experience building and deploying models using scalable serving frameworks (e.g., REST APIs, containerized deployments, or cloud-based inference services).
  • Experience working with large-scale structured and unstructured datasets.
  • Strong understanding of machine learning concepts including supervised/unsupervised learning, deep learning, model evaluation, and feature engineering.
  • Experience working in the federal government or other highly regulated environments with security and compliance requirements.
  • Strong analytical and problem-solving skills.
  • Ability to communicate complex technical concepts to non-technical stakeholders.
  • Strong collaboration skills across engineering, data, and product teams.
  • Ability to work independently in a fast-paced, mission-driven environment.
  • High attention to detail with a focus on model reliability and production readiness.
  • US Citizenship or Permanent Residency required.
  • Must reside in the Continental US.
  • Depending on the government agency, specific requirements may include public trust background check or security clearance.

Preferred Qualifications
  • Experience deploying models in cloud environments (AWS, Azure, or GCP).
  • Familiarity with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI).
  • Experience with streaming or real-time inference systems.
  • Background in predictive maintenance, anomaly detection, or operational analytics use cases.
  • Familiarity with Docker, Kubernetes, and CI/CD pipelines for machine learning systems.
  • Experience supporting healthcare (e.g., CMS), or other federal mission systems.
  • Qualified individuals living in HUBZone-certified areas are strongly encouraged to apply. To find out if you live in a HUBZone go to: https://maps.certify.sba.gov/hubzone/map#center=44.722800,-103.249700&zoom=4.

$135,000 - $145,000 a year
The likely salary range for this position is $135,000-$145,000. The salary offered will depend on several factors including, but not limited to, relevant experience, skills, education, geographic location, internal equity, business needs, and other factors permitted by law. Posted pay ranges are a general guideline only and are not a guarantee of compensation or salary.
Our People
We invest in the lives of our employees, both in and out of the workplace, by providing competitive pay and benefits packages. Benefits offered may include health care, dental, vision, life insurance; 401(k); paid time off including PTO, holidays, and any other paid leave required by law.
Location
Be in your Element. We are a remote first company based out of Washington, DC. As a HUBZone-certified business we are committed to supporting local economic development.
Element is an equal opportunity employer All qualified applicants will receive consideration for employment without regard to age, ancestry, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status, marital status, protected veteran status, or any other legally protected class.
We believe in a world where solutions we build improve the lives of those who use them.

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