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Machine Learning Algorithms Jobs (NOW HIRING)

Quanta Search

Machine Learning Engineer

Manhattan, NY · On-site

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 ...

CoVar

Machine Learning Engineer

Durham, NC · On-site

The Machine Learning Engineer will develop software and machine learning algorithms to address real-world customer issues and will have opportunities to present their work to high-level customers.

CoVar

Machine Learning Engineer

Durham, NC · On-site

In this role, you will help develop software and machine learning algorithms to address real-world customer challenges, working closely with data and presenting your findings to high-level customers.

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

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 ...

RAPID EAGLE INC

Machine Learning Engineer

Sunnyvale, CA · Remote

$70 - $80/hr

The ideal candidate will have strong expertise in machine learning algorithms, data engineering, model deployment, and cloud technologies. Key Responsibilities: * Design, develop, and deploy machine ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

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 ...

Photon

Machine Learning Engineer - NJ

Dallas, TX

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

Skild AI

Machine Learning Engineer

Pittsburgh, PA

$100K - $300K/yr

Machine Learning Engineer San Mateo, Pittsburgh Company Overview At Skild AI, we are building the ... Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.

Skild AI

Machine Learning Engineer

San Mateo, CA

$100K - $300K/yr

Machine Learning Engineer San Mateo, Pittsburgh Company Overview At Skild AI, we are building the ... Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.

Skild AI

Machine Learning Engineer

San Mateo, CA

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 ...

Samprasoft

Machine Learning Engineer

Mclean, VA

Design and implement Machine Learning algorithms and models into software solutions for our enterprise customers by using common machine learning frameworks, including establishing and training ...

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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 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 Engineer

Quanta Search

Manhattan, NY

Other

Posted 28 days ago

Job description

Our client is a process driven investment management group consisting of a team of researchers, traders and technologists who harness and apply the power of technology and automation to identify, model and trade global financial markets. Thisdivision offers an array of quantitative investment fund products to its clients.
They are seeking candidates with exceptional academic credentials to join theirteam and participate in and support of the firm's efforts in the research, trading and production processes.
They look for candidates who are eager to make an impact by doing real, hands-on research and development. Candidates must possess exceptional knowledge of mathematical and statistical methods as well as a proven ability to solve complex problems. A desire to work with large data sets and apply creative thinking is required. Successful candidates will also have deep interest in learning about trading and the financial markets.
They offera supportive environment that fosters independent thought in a collegial, results oriented, work setting. Researchers and developers there are passionate about their work, model building, data and technology.
You are curious and intellectually driven to succeed. You'll beprovidedwith the tools, resources and training required to satisfy that curiosity and passion, leading them to new insights and discoveries. Theirprocess driven approach enables these insights to be thoroughly tested in a systematic fashion and ultimately, if confirmed, integrated into theportfolio.
Role:
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 computing. Machine Learning Engineers should be comfortable with data engineering and should have an interest in the data science.
What they will do:
They will be responsible for their production grade signal generation and ML systems. They can act as data scientists, but should be comfortable pushing their algorithms, models, and signals into production.
Minimum Requirements:
  • Strong understanding of statistical analysis and computational modelling.
  • Strong understanding of algorithms and data structures.
  • Familiar with map reduce and big data processing (Spark, Hadoop, DataFlow, etc).
  • TensorFlow (or another GPU integrated deep learning library).
  • Deep understanding of machine learning algorithms.
  • Deep understanding of numerical optimization.
  • Strong understanding of data structures and algorithms.
Plus, but not required:
  • Previous experience in tech industry (GOOG, AMZN, FB, NFLX, Spotify, etc).
  • Experience building industrial grade ETL pipelines.
  • Experience building frontend systems.
  • Familiarity with dashboards and other visualization tools.
  • Ability to derive generalization bounds for common ML algorithms.
  • Experience developing new machine learning algorithms.

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