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Remote Machine Learning Researcher Jobs in Orange, NJ

Senior Product Manager, Recommendations

New York, NY ยท On-site +1

$138K - $182K/yr

ML/AI - you have meaningful experience with machine learning retrieval and/or ranking systems ... Remote candidates outside commutable distance may be considered on a case-by-case basis, with the ...

Senior Staff Machine Learning Engineer

Brooklyn, NY ยท On-site +1

$109K - $150K/yr

We are a team of researchers, engineers, and data scientists dedicated to solving the complex ... Remote candidates outside commutable distance may be considered on a case-by-case basis, with the ...

You'll apply expertise in machine learning, statistics, experimentation, and data analysis to ... Data Modeling Preferred Qualifications * 1+ year of experience in technology, finance, research, or ...

Apply statistical and machine-learning techniques to generate, validate, and improve trading ... Build and operate data pipelines and research platforms for high-quality, reproducible research.

Showing results 41-60

Remote Machine Learning Researcher information

See Orange, NJ salary details

$30.4K

$114.8K

$166.9K

How much do remote machine learning researcher jobs pay per year?

As of Sep 15, 2026, the average yearly pay for remote machine learning researcher in Orange, NJ is $114,759.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,000.00 and $156,300.00 per year, depending on experience, location, and employer.

What is a remote machine learning researcher?

Remote Machine Learning Researchers are professionals who study, design, and develop machine learning algorithms and models while working outside of a traditional office environment. They typically analyze data, conduct experiments, and collaborate with teams or organizations virtually to advance artificial intelligence technologies. Their work may involve tasks such as building predictive models, publishing research papers, or contributing to open-source machine learning projects. Being remote allows them flexibility in location and often the ability to work with international teams. Strong programming, mathematical, and communication skills are essential in this role.

What are the key skills and qualifications needed to thrive as a remote machine learning researcher?

To thrive as a Remote Machine Learning Researcher, you need a strong background in mathematics, statistics, programming (Python, R), and a relevant advanced degree such as a Master's or Ph.D. in computer science or a related field. Familiarity with machine learning frameworks (TensorFlow, PyTorch), cloud computing platforms, and version control systems (Git) is typically required, along with published research or contributions to academic conferences. Outstanding problem-solving ability, self-motivation, and excellent written communication are crucial soft skills for remote collaboration and knowledge sharing. These skills are essential for developing innovative models, contributing to cutting-edge research, and effectively collaborating in a distributed team environment.

What are the common challenges faced by remote machine learning researchers when collaborating with global teams?

Remote machine learning researchers often collaborate with team members across different time zones and cultural backgrounds, which can make synchronous meetings and real-time problem-solving challenging. Communication of complex ideas, such as model architectures or experimental results, may require extra effort through detailed documentation and regular virtual check-ins. However, most organizations use collaborative tools like version control systems, project management platforms, and video conferencing to bridge these gaps, ensuring that research progress stays on track and team members remain aligned.

Sr. Lead Machine Learning Engineer/Remote

Paterson, NJ โ€ข Remote

Apetan Consulting llc
IT Servicesย โ€ขย 1 - 10 employees

$80 - $150/hr

Contractor

Re-posted 9 hours 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.