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Machine Learning Ai Jobs (NOW HIRING)

Jobtailor

Director of Machine Learning

Washington, DC · On-site

$180 - $260/hr

Communicate technical progress, risks, and ROI, linking AI team output to revenue and mission ... Machine Learning Engineering Leadership * Production Deployment Experience * Python Proficiency

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Machine Learning Ai information

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$25.5K

$42.6K

$88K

How much do machine learning ai jobs pay per year?

As of Aug 21, 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 is a machine learning AI?

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 are the key skills and qualifications needed to thrive as a machine learning AI?

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?

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 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 are the most commonly searched types of Machine Learning Ai jobs?

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What states have the most Machine Learning Ai jobs?

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Machine Learning Ai jobs near you
Infographic showing various Machine Learning Ai job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

AI Research Scientist - Machine Learning

AIToolboard

Richmond, VA • On-site

$120 - $190/hr

Other

Posted 3 days ago

New

Job description

Jobs / AI Research Scientist - Machine Learning

AI Research Scientist - Machine Learning

Full-time

About the Role

Our client is seeking a brilliant and innovative AI Research Scientist specializing in Machine Learning to join their cutting-edge R&D team in Richmond, Virginia, US. This role is at the forefront of developing next-generation AI technologies and algorithms. You will be responsible for designing, implementing, and evaluating advanced machine learning models, conducting groundbreaking research, andcontributing to high-impact AI applications. The ideal candidate possesses a strong academic background, a deep understanding of ML principles, and a passion for pushing the boundaries of artificial intelligence.Key Responsibilities:Conduct advanced research in machine learning, deep learning, and related AI fields. Design, develop, and implement novel algorithms and models for complex AI problems. Experiment with various ML techniques, including supervised, unsupervised, reinforcement learning, and neural networks. Analyze large datasets, preprocess data, and extract meaningful features for model training. Evaluate model performance, identify areas for improvement, and iterate on designs. Collaborate with software engineers to deploy and integrate AI models into production systems. Stay current with the latest advancements in AI and ML research through literature review and conference participation. Publish research findings in leading scientific journals and present at conferences. Mentor junior researchers and interns, fostering a collaborative research environment. Contribute to the intellectual property portfolio through patent applications.Qualifications:Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field. Proven research experience demonstrated through publications in top-tier AI/ML conferences and journals (e.g., NeurIPS, ICML, ICLR, CVPR). Strong theoretical foundation in machine learning, deep learning, and statistical modeling. Proficiency in programming languages such as Python, and experience with ML libraries like TensorFlow, PyTorch, scikit-learn. Experience with data manipulation and analysis tools. Ability to design and conduct rigorous experiments, interpret results, and draw insightful conclusions. Excellent problem-solving skills and creativity in developing novel solutions. Strong communication and presentation skills, with the ability to articulate complex technical concepts. Experience with distributed computing frameworks (e.g., Spark) is a plus. Experience in specific domains like NLP, computer vision, or reinforcement learning is highly desirable. Join a forward-thinking team that is shaping the future of AI. This exciting opportunity is based in Richmond, Virginia, US .

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