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

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Remote Machine Learning information

See Dunmore, PA salary details

$25.3K

$42.2K

$87.3K

How much do remote machine learning jobs pay per year?

As of Jun 10, 2026, the average yearly pay for remote machine learning in Dunmore, PA is $42,242.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,600.00 per year, depending on experience, location, and employer.

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.

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.

Is ML full of coding?

Machine Learning (ML) roles often involve significant coding, especially in programming languages like Python or R, to develop algorithms and models. However, some positions focus more on data analysis, feature engineering, or model evaluation, which may require less coding but still involve technical skills and understanding of ML concepts.
More about Remote Machine Learning jobs
What cities near Dunmore, PA are hiring for Remote Machine Learning jobs? Cities near Dunmore, PA with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
AVP of Data Platform Services Engineering & DevOps

AVP of Data Platform Services Engineering & DevOps

Berkshire Hathaway GUARD Insurance Companies

Wilkes Barre, PA • On-site, Remote

$127K - $313K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 13 days ago

Job description

Good things are happening at Berkshire Hathaway GUARD Insurance Companies—an A+ (Superior) rated, nationwide Property & Casualty insurer backed by Berkshire Hathaway. With supportive leadership, collaborative teams, and opportunities to grow, GUARD is a place where people build meaningful, longterm careers.


Good Things You Can Count On.
•  Hybrid schedule: 2 days remote / 3 inoffice
•  Predictable hours (no nights, weekends, or holidays)
•  Competitive pay + generous PTO
•  Medical, dental & vision starting day one
•  401(k), tuition reimbursement & longevity bonuses


Shape, code and scale next-gen data services on cutting-edge DnA Platform!

At Berkshire Hathaway GUARD, we’re not just insuring-we’re innovating. Our Data & Analytics (DnA) organization is at the heart of transforming how we assess risk, serve customers, and shape the future of insurance. We’re seeking AVP of Data Platform Services - Engineering & DevOps to lead the execution of our most strategic data initiatives.
This role will own and drive two core service pillars of our platform:

  1. Data Engineering & Integration Services
    • Enable customers to ingest, transform, and manage data pipelines using Microsoft Fabric workloads (Data Factory, Lakehouse, etc..).
  2. DevOps, CI/CD, MLOps & LLMOps Services
    • Deliver automation and operational excellence for deploying data and AI solutions.
    • Implement CI/CD pipelines for Fabric workloads, manage MLOps for model lifecycle, and establish LLMOps for generative AI solutions.

This is a hands-on leadership role—you will build and maintain code, templates, and technical assets within Microsoft Fabric workloads, while scaling services and leading a team.

What You’ll Do

  • Hands-On Development: Design, build, and maintain reusable code, deployment templates, and automation scripts for Fabric workloads.
  • Service Ownership: Define, manage, and continuously improve Data Engineering and DevOps/MLOps/LLMOps service lines.
  • Customer Success: Partner with colleagues in the platform and as well as the domain senior engineers to deliver tailored solutions and ensure adoption of best practices.
  • Team Leadership: Mentor a team of engineers and architects.
  • Innovation: Drive automation, governance, and operational excellence across services.
  • Collaboration: Align services with Platform product roadmap and work closely with Domain Success teams.

 

KPIs & Success Metrics

  • Service Delivery: 95%+ on-time delivery of service features and enhancement requests.
  • Automation Coverage: 90%+ of deployments automated via CI/CD pipelines.
  • Customer Satisfaction: Maintain CSAT score of 4.5+/5 for service engagements.
  • Operational Efficiency: Reduce deployment cycle time by 50% within 12 months.
  • Innovation Impact: Launch at least 2 new automation or optimization features per quarter.

The successful candidate is expected to work in one of our offices 3 days per week and also be available for travel as required.

The annual base salary range posted represents a broad range of salaries around the U.S. and is subject to many factors including but not limited to credentials, education, experience, geographic location, job responsibilities, performance, skills and/or training.

Qualifications

  • Experience: 10+ years in data engineering, DevOps, or platform services; 5+ years in leadership roles.
  • Expertise: Strong knowledge of Microsoft Fabric, Azure DevOps, CI/CD, MLOps frameworks, and modern data architectures.
  • Hands-On Skills: Proficiency in Python, SQL, PowerShell, and Fabric APIs.
  • Leadership: Proven ability to scale teams and deliver enterprise-grade solutions.
  • Strategic Thinking: Ability to translate business objectives into technical solutions and service offerings.
  • Strong mentoring and communication skills
  • Insurance industry experience preferred
  • Bonus: Experience with data product or AI product delivery and data mesh models

Salary Range $127,053-$313,842.10 + bonus 

In accordance with applicable pay transparency laws, this range represents a good-faith estimate. Final compensation will be determined based on factors such as experience, credentials, geographic location, and other considerations permitted by law.

This role may be based out of any of our office locations, including:

New York, NY; Parsippany, NJ; Conshohocken, PA; WilkesBarre, PA; Alpharetta, GA; Rosemont, IL; Plano, TX; Scottsdale, AZ 

Applicants must be authorized to work in the U.S. without current or future sponsorship.

Apply