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Machine Learning Algorithms Jobs (NOW HIRING)

Machine Learning Engineers build production grade machine learning algorithms that operate in real time or at scale. They have a very deep understanding of machine learning algorithms and cloud ...

... algorithms but also robustness monitoring and system logging/alarming. We seek talented and motivated students and recent graduates with a strong background in machine learning, deep learning ...

Manage machine learning algorithm lifecycle. * Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning ...

Manage machine learning algorithm lifecycle. * Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning ...

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

Develop machine learning algorithms to drive personalized customer experiences and provide actionable business insights. * Apply expertise in data mining and machine learning techniques, including ...

Machine Learning Engineer - NJ

Addison, TX

$54 - $71.50/hr

Develop machine learning algorithms to drive personalized customer experiences and provide actionable business insights. * Apply expertise in data mining and machine learning techniques, including ...

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Machine Learning Algorithms information

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$25.5K

$42.6K

$88K

How much do machine learning algorithms jobs pay per year?

As of May 30, 2026, the average yearly pay for machine learning algorithms 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 Algorithms Engineer, and why are they important?

To excel as a Machine Learning Algorithms Engineer, you need a solid background in mathematics, statistics, programming (especially Python or R), and a relevant degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow, PyTorch, or scikit-learn), data preprocessing tools, and cloud platforms is typically required, along with knowledge of version control systems. Strong analytical thinking, problem-solving abilities, and effective communication skills set top performers apart in this role. These skills and qualities are critical for designing robust models, collaborating with cross-functional teams, and translating complex data into actionable solutions.

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

As a Machine Learning Algorithms specialist, collaborating with cross-functional teams such as data engineers, software developers, and product managers can present challenges like aligning on project goals, communicating complex technical concepts to non-experts, and integrating models into existing systems. It's important to establish clear communication channels, define shared objectives early, and actively participate in iterative feedback cycles. These practices help ensure that machine learning solutions are both technically sound and aligned with business needs.

What are machine learning algorithms?

Machine learning algorithms are computational methods that enable computers to learn patterns and make decisions or predictions from data without being explicitly programmed for each task. These algorithms can be classified into categories such as supervised learning, unsupervised learning, and reinforcement learning, each suited for different data and goals. Examples include decision trees, support vector machines, neural networks, and clustering algorithms. The choice of algorithm depends on the type of problem, the nature of the data, and the desired outcome.

Which 3 jobs will survive AI?

Machine Learning Algorithms roles are likely to persist as they involve designing, developing, and maintaining AI systems, requiring specialized skills in programming, statistics, and domain knowledge. Jobs that require complex problem-solving, creativity, and emotional intelligence, such as data scientists, AI ethics specialists, and AI system architects, are also expected to remain in demand despite advances in AI automation.

What is the difference between Machine Learning Algorithms vs Data Scientists?

AspectMachine Learning AlgorithmsData Scientists
CredentialsKnowledge of algorithms, programming, statisticsAdvanced degrees in data science, statistics, or related fields
Work EnvironmentDeveloping, testing, and tuning algorithmsAnalyzing data, building models, interpreting results
Industry UsageEmbedded within data science workflows and toolsLeading data analysis projects, decision-making

While machine learning algorithms are the core tools used by data scientists, the role of a data scientist encompasses understanding, applying, and interpreting these algorithms within broader data analysis and business contexts. Machine learning algorithms are technical components, whereas data scientists integrate these tools to derive insights and inform strategies.

More about Machine Learning Algorithms jobs
What cities are hiring for Machine Learning Algorithms jobs? Cities with the most Machine Learning Algorithms job openings:
What states have the most Machine Learning Algorithms jobs? States with the most job openings for Machine Learning Algorithms jobs include:
Infographic showing various Machine Learning Algorithms job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 60% In-person, and 40% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Engineer

Your Personal AI

San Francisco, CA • On-site, Remote

Full-time

Posted 8 days ago


Job description

We are looking for a highly skilled and innovative Machine Learning Engineer to join our dynamic team at Your Personal AI. In this role, you will be responsible for designing, developing, and deploying state-of-the-art machine learning models that drive the core of our AI-driven solutions. You will collaborate closely with cross-functional teams to identify challenges, create scalable algorithms, and implement machine learning systems that solve real-world problems.
Machine Learning Engineer at Your Personal AI
We are looking for a talented Machine Learning Engineer to join our AI Research and Development department at Your Personal AI. As a Machine Learning Engineer, you will be responsible for developing and implementing machine learning algorithms to enhance our AI technologies.
Your main tasks will include analyzing and interpreting complex data sets, collaborating with cross-functional teams to design and deploy machine learning models, and continuously improving our AI systems.
  • Develop and implement machine learning algorithms
  • Analyze and interpret complex data sets
  • Collaborate with cross-functional teams
  • Design and deploy machine learning models
  • Continuously improve AI systems

If you are passionate about AI and have a strong background in machine learning, we would love to hear from you. Join us at Your Personal AI and be part of a dynamic team driving innovation in artificial intelligence.
Job Requirements for Machine Learning Engineer at Your Personal AI
Please ensure that the job requirements for the Machine Learning Engineer role at Your Personal AI in the AI Research and Development department include the following:
  • Strong proficiency in machine learning algorithms and techniques
  • Experience with programming languages such as Python, R, or Java
  • Ability to work with large datasets and perform data analysis
  • Knowledge of deep learning frameworks like TensorFlow or PyTorch
  • Experience in developing and deploying machine learning models
  • Strong problem-solving skills and analytical thinking
  • Excellent communication and teamwork abilities