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Remote Machine Learning Jobs in Exton, PA (NOW HIRING)

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Data Scientist III

Philadelphia, PA · On-site +1

$110K - $115K/yr

Analyze vast amounts of unstructured data and design, prototype, and operationalize machine learning and automation solutions for our health business. Provide data analytics support including ...

Data Scientist III

Philadelphia, PA · On-site +1

$110K - $115K/yr

Analyze vast amounts of unstructured data and design, prototype, and operationalize machine learning and automation solutions for our health business. Provide data analytics support including ...

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Azure Data Architect

Malvern, PA · Remote

$65 - $84.75/hr

Remote Duration: Long Term Contract Visa- Only US Citizen, H4 EAD, L2S, TN Visa Experience: 12 to ... Experience in creating Data warehouse, data lakes for Reporting, AI and Machine Learning

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

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Remote Machine Learning information

See Exton, PA salary details

$24.6K

$41.1K

$84.9K

How much do remote machine learning jobs pay per year?

As of Jul 3, 2026, the average yearly pay for remote machine learning in Exton, PA is $41,099.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,400.00 and $44,400.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
What cities near Exton, PA are hiring for Remote Machine Learning jobs? Cities near Exton, PA with the most Remote Machine Learning job openings:

Enterprise Solutions Graph Database

H R PUNDITS INC

Collegeville, PA • On-site, Remote

Full-time

Posted 11 hours ago


Job description

Job title : Enterprise Solutions Graph Database/ Architect
Location: Upper Providence Township, PA
(Onsite/Remote )
Experience : 15 Years
Role Overview
Seeking a seasoned Graph Database
Knowledge Graph Expert to perform a comprehensive study of our existing platform. Evaluate our current architecture, data ontology, and query performance to provide a strategic roadmap. The goal is to evolve our Knowledge Graph into a robust, scalable engine that accelerates different Pharma areas ( drug discovery, clinical insights, and cross-departmental data democratization)
Required Qualifications
Graph Expertise: 10+ years of experience with Graph Databases. Deep proficiency in LPG (Labeled Property Graphs) or RDF/Triple Stores.
Pharma Domain Knowledge: Proven experience handling biomedical data types (e.g., Gene-Disease associations, Chemical compounds, Patient journeys).
Semantic Web Standards: Strong understanding of Linked Data principles, URI strategies, and ontology modeling.
Data Engineering: Experience with ETL/ELT pipelines that feed graphs from unstructured (PDF publications) and structured (EDC, LIMS) sources.
Advanced Analytics: Experience implementing Graph Data Science algorithms (centrality, community detection) or integrating Graphs with Machine Learning.
Technical Stack Preferences
Graph DBs: AnzoGraph, Neo4j, Stardog,
Languages: Python, Java, SPARQL, Cypher, or Gremlin.
Bio-Ontologies: Familiarity with OBO Foundry, ChEMBL, or Ensembl.