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Technical Support Engineer Remote Jobs in Randolph, NJ

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Clarity Developer

Newark, NJ · Remote

Remote (Preferred: Raleigh, NC or New Jersey - hybrid 3 days/week) Schedule: Must be able to work ... Collaborate with end-users to gather requirements and provide technical support. * Manage system ...

ME&P Management Inc

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Mechanical Project & Design Engineer

Summit, NJ · Remote

$120K - $160K/yr

... for supporting engineering design efforts across projects while providing technical guidance to ... Our hybrid work model combines remote flexibility with in-person collaboration at project sites and ...

ME&P Management Inc

Be Seen First

Mechanical Project & Design Engineer

Summit, NJ · Remote

$120K - $160K/yr

... for supporting engineering design efforts across projects while providing technical guidance to ... Our hybrid work model combines remote flexibility with in-person collaboration at project sites and ...

ABB

Protection and Control Engineer

Cedar Knolls, NJ · Remote

While this is a full remote position, there is preference for candidates located in the Northern ... technical issue resolution while providing ongoing communication, status updates, and support to ...

CP Engineers

Water Resources Project Manager

Sparta, NJ · On-site +1

$120K - $160K/yr

At CP Engineers, we don't just execute projects, we build careers. Remote work flexibility ... Technical Support: Provide technical guidance in the planning, design, and permitting of water and ...

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All JobsTechnical Support Engineer JobsTechnical Support Engineer Remote JobsTechnical Support Engineer Remote Jobs in Randolph, NJ

Technical Support Engineer Remote information

See Randolph, NJ salary details

$38.5K

$81.2K

$122.8K

How much do technical support engineer remote jobs pay per year?

As of Aug 6, 2026, the average yearly pay for technical support engineer remote in Randolph, NJ is $81,230.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,600.00 and $101,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a technical support engineer remote, and why are they important?

To thrive as a Technical Support Engineer Remote, you need strong problem-solving abilities, technical troubleshooting expertise, and a background in IT or computer science, often supported by relevant certifications like CompTIA A+ or Microsoft Certified Solutions Expert (MCSE). Familiarity with ticketing systems, remote desktop tools, and diagnostic software is essential for effective support. Exceptional communication skills, patience, and the ability to work independently are crucial soft skills in a remote environment. These qualities enable efficient resolution of technical issues, ensure customer satisfaction, and maintain seamless remote operations.

What is the difference between Technical Support Engineer Remote vs Technical Support Specialist?

AspectTechnical Support Engineer RemoteTechnical Support Specialist
Required CredentialsTypically requires a degree in IT, Computer Science, or related field; certifications like CompTIA A+ or Network+ are commonOften requires similar certifications; may have less emphasis on formal degrees
Work EnvironmentRemote, often supporting enterprise clients or internal teams via online toolsCan be remote or on-site; supports customers via phone, email, or chat
Employer & Industry UsageUsed across tech companies, SaaS providers, and IT service firmsCommon in tech, retail, and telecommunications industries

Both roles involve troubleshooting technical issues, but Technical Support Engineer Remote typically requires more technical expertise and handles complex problems remotely, while Technical Support Specialist may focus on basic support and customer service. The roles often overlap, but the engineer position usually demands a higher technical skill level and certifications.

What does a technical support engineer do in a remote role?

A Technical Support Engineer working remotely provides assistance to customers or internal teams in resolving technical issues related to software, hardware, or network systems. They diagnose problems, offer troubleshooting guidance, and may escalate complex issues to higher-level engineers. Communication is typically done through email, chat, or video calls, ensuring users can continue their work with minimal disruption. Remote Technical Support Engineers must be skilled in problem-solving, customer service, and using various support tools. Their goal is to help users resolve issues efficiently, regardless of their physical location.

What are some typical challenges faced by technical support engineers working remotely, and how can they be managed?

Remote Technical Support Engineers often face challenges such as troubleshooting complex technical issues without in-person access to customer systems and maintaining clear communication across different time zones. To manage these, effective use of remote access tools, thorough documentation, and proactive communication with both customers and team members are crucial. Additionally, setting up a dedicated workspace and establishing structured routines can help maintain productivity and work-life balance. Regular virtual meetings and collaboration platforms also support knowledge sharing and team cohesion.
More about Technical Support Engineer Remote jobs
What cities near Randolph, NJ are hiring for Technical Support Engineer Remote jobs? Cities near Randolph, NJ with the most Technical Support Engineer Remote job openings:
Technical Support Engineer Remote jobs near you

Sr. Lead Machine Learning Engineer/Remote

Apetan Consulting llc

Paterson, NJ • Remote

$80 - $150/hr

Contractor

Re-posted 20 days ago

Job description

Sr. Lead Machine Learning EngineerLocation-RemoteJob Summary

The Sr. Lead Machine Learning Engineer is responsible for leading the design, development, deployment, and optimization of machine learning solutions that drive business value. This role combines technical expertise, strategic leadership, and cross-functional collaboration to build scalable AI/ML systems, mentor engineering teams, and guide the organization's machine learning initiatives.

Key Responsibilities
  • Lead the development and deployment of machine learning models and AI-driven solutions.
  • Design scalable ML architectures, pipelines, and production-ready systems.
  • Collaborate with data scientists, software engineers, product managers, and business stakeholders to define and deliver ML solutions.
  • Oversee data preparation, feature engineering, model training, evaluation, and monitoring processes.
  • Optimize model performance, scalability, reliability, and operational efficiency.
  • Establish best practices for MLOps, model governance, testing, and deployment.
  • Conduct code reviews and provide technical leadership and mentorship to engineering teams.
  • Evaluate emerging AI/ML technologies and recommend innovative solutions.
  • Ensure compliance with security, privacy, and responsible AI standards.
  • Support production systems by troubleshooting and resolving complex ML-related issues.
  • Drive technical roadmaps and contribute to strategic AI initiatives.
Required Qualifications
  • Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
  • 8+ years of software engineering experience, including 5+ years in machine learning engineering.
  • Strong proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Experience building and deploying machine learning models in production environments.
  • Strong knowledge of data structures, algorithms, statistics, and machine learning techniques.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud.
  • Knowledge of MLOps tools, CI/CD pipelines, and model monitoring practices.
  • Excellent leadership, communication, and problem-solving skills.
Preferred Qualifications
  • Master’s degree or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
  • Experience with large-scale distributed systems and big data technologies.
  • Knowledge of Generative AI, Large Language Models (LLMs), NLP, computer vision, or recommendation systems.
  • Experience with Kubernetes, Docker, and cloud-native architectures.
  • Prior experience leading technical teams and enterprise AI initiatives.