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Machine Learning Algorithms Jobs (NOW HIRING)

CoVar

Machine Learning Engineer

Durham, NC

Machine Learning Engineer About CoVar CoVar is a small AI/ML R&D software company in Durham, NC ... You will work with data, develop algorithms, evaluate results, and write the production code that ...

SAIC

Machine Learning Developer

Arlington, VA · On-site

Develop and implement machine learning models and algorithms to provide suggested values to readiness reports for our DOD client. * Refine data collection processes and improve data quality. * Design ...

Nanite Inc.

Machine Learning Engineer

Boston, MA · On-site

Apply and deploy established and novel statistical and machine learning algorithms to explore, understand and optimize properties of the vast delivery vehicle space, both in silico and experimentally

Nanite Inc.

Machine Learning Engineer

Boston, MA

Apply and deploy established and novel statistical and machine learning algorithms to explore, understand and optimize properties of the vast delivery vehicle space, both in silico and experimentally

Givzey

Machine Learning Engineer

Design, develop, and implement machine learning models and algorithms * Analyze large datasets and extract meaningful insights * Collaborate with cross-functional teams to integrate ML solutions into ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

In this role, you will innovate foundational machine learning algorithms for computational photography and computer vision, to research, design and qualify novel cameras and sensors for future Apple ...

Navstar

Machine Learning Engineer

Centreville, VA

$102K - $144K/yr

Duties * Support development of computer vision and machine learning (ML) algorithms capable of object detection, classifying, localizing, and tracking objects of interest from a variety of ...

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$25.5K

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How much do machine learning algorithms jobs pay per year?

As of Jun 19, 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 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.

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 engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or at large tech companies can earn salaries of $500,000 or more, including base pay, bonuses, and stock options. Achieving this level typically requires a strong educational background, specialized certifications, and a track record of successful projects.

Which 3 jobs will survive AI?

Machine learning engineers, data scientists, and AI specialists are likely to continue thriving as AI advances because they develop, interpret, and improve AI systems. These roles require specialized skills in programming, statistical analysis, and domain expertise that are difficult to fully automate. Continuous learning and staying updated with new tools like TensorFlow or PyTorch are essential for these jobs.

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.

Is ML a high paying job?

Machine Learning (ML) jobs are generally well-paid due to the specialized skills required, such as programming, data analysis, and knowledge of algorithms. Salaries vary based on experience, location, and industry, but many ML roles offer competitive compensation compared to other tech positions.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in algorithms, data science, and deep learning. These positions usually involve leadership responsibilities, extensive experience, and may be located in competitive tech hubs or large organizations with substantial AI investments.

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.
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Machine Learning Algorithms jobs near you
Machine Learning Developer

Machine Learning Developer

Science Applications International Corporation

Arlington, VA • Hybrid

Other

This job post has expired today. Applications are no longer accepted.

SAIC rating

7.8

Company rating: 7.8 out of 10

Based on 78 frontline employees who took The Breakroom Quiz

70th of 204 rated it services

Job description

SAIC is seeking a talented and experienced Machine Learning Developer to join our dynamic team.

This position is hybrid in Arlington, VA with 2-3 days per week onsite at the Pentagon or the Mark Center.

The ideal candidate will have a strong background in computer science, software engineering, and experience with machine learning algorithms and frameworks. The Machine Learning Developer will collaborate with software engineers to create innovative ML/AI solutions, improve predictive models, and deploy machine learning systems into production.

Key Responsibilities:

  • Develop and implement machine learning models and algorithms to provide suggested values to readiness reports for our DOD client.
  • Refine data collection processes and improve data quality.
  • Design and develop scalable machine learning solutions for various applications.
  • Work with software developers to integrate machine learning models into production systems.
  • Conduct research to identify new approaches and methods for machine learning and AI.
  • Stay updated with the latest trends and advancements in machine learning and AI.
  • Document processes, codes, and workflows for future reference and reproducibility.
  • Provide support and maintenance for deployed machine learning systems. 
SAIC is a premier mission integrator focused on advancing the power of technology and innovation to serve and protect our world. Our robust portfolio of offerings across the defense, space, intelligence, and civilian markets includes secure high-end solutions in mission IT, enterprise IT, engineering services, and professional services. We integrate emerging technology, rapidly and securely, into mission critical operations that modernize and enable critical national imperatives.

We are approximately 23,000 strong; driven by mission, united by purpose, and inspired by opportunities. SAIC is an Equal Opportunity Employer. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $7.3 billion. For more information, visit saic.com. For ongoing news, please visit our newsroom.

Required Education:

  • Bachelors and five (5) years or more experience; Masters and three (3) years or more experience; PhD and zero (0) years related experience; four (4) years of experience considered in lieu of degree.

Qualifications:

  • Proven experience designing, developing, and deploying OpenAI solutions as a Machine Learning Developer or in a similar role.
  • Strong programming skills in Python, R, C#, Java or similar languages.
  • Experience with deep learning techniques and models.
  • Expertise in natural language processing (NLP) or computer vision.
  • Proficiency with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-Learn, etc.
  • Experience with data preprocessing, data mining, and data visualization techniques.
  • Strong analytical and problem-solving skills.
  • Excellent communication and teamwork abilities.
  • Familiarity with software development best practices and source control (e.g., Git).

Clearance:

  • Active Secret clearance is required for this position.

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