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Manager Remote Machine Learning Engineer Jobs in Mantua, NJ

Soni Resources

Data Scientist

Conshohocken, PA · On-site +1

$175K/yr

Remote (Preference for Northeast/Mid-Atlantic; monthly travel to Plymouth Meeting, PA as needed ... Experience collaborating closely with Data Engineering teams or supporting machine learning ...

Melior

AI Program Manager (Remote)

Philadelphia, PA · Remote

$90K - $130K/yr

... change management required to turn tool access into real, lasting behavior change. * Custom AI ... We engineer purpose-built AI workflows and agents for our clients' highest-value problems - from ...

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Showing results 21-40

All JobsMachine Learning Engineer JobsManager Remote Machine Learning Engineer JobsManager Remote Machine Learning Engineer Jobs in Mantua, NJ

Manager Remote Machine Learning Engineer information

See Mantua, NJ salary details

$28.6K

$64.3K

$108.3K

How much do manager remote machine learning engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for manager remote machine learning engineer in Mantua, NJ is $64,321.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,700.00 and $69,800.00 per year, depending on experience, location, and employer.

What is a manager remote machine learning engineer?

A Manager Remote Machine Learning Engineer is a leadership role responsible for overseeing a team of machine learning engineers who work remotely. They manage the development, deployment, and optimization of machine learning models and ensure that projects align with organizational goals. In addition to technical expertise, this manager focuses on remote team collaboration, communication, and productivity. They often coordinate workflows, mentor team members, and act as a bridge between technical teams and business stakeholders.

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

AspectManager Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience in ML engineeringBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentRemote, collaborative teams, focus on ML model deploymentRemote or on-site, data analysis, model development, research
Employer & Industry UsageTech companies, AI startups, large enterprisesTech, finance, healthcare, research institutions
Search & Comparison IntentUnderstanding managerial roles in ML teamsData analysis, modeling, research tasks

The Manager Remote Machine Learning Engineer oversees ML projects and teams, focusing on deployment and management, while Data Scientists primarily analyze data and develop models. Both roles require strong technical skills, but the manager role emphasizes leadership and project oversight.

What are the key skills and qualifications needed to thrive as a manager remote machine learning engineer, and why are they important?

To thrive as a Manager Remote Machine Learning Engineer, strong expertise in machine learning algorithms, programming (Python, R), and a degree in computer science or a related field are essential, along with proven leadership experience. Familiarity with cloud platforms (AWS, Azure, GCP), ML frameworks (TensorFlow, PyTorch), and project management tools is typically required, as well as certifications such as AWS Certified Machine Learning or Google Professional Machine Learning Engineer. Outstanding communication, team leadership, and problem-solving skills help foster collaboration and drive remote teams toward project goals. These capabilities are vital for effectively managing distributed teams, delivering robust AI solutions, and ensuring project success in a remote environment.

How does a manager remote machine learning engineer typically balance team leadership with hands-on technical responsibilities?

A Manager Remote Machine Learning Engineer often splits time between leading and mentoring a distributed team and actively contributing to machine learning projects. While overseeing project timelines, conducting code reviews, and setting technical direction are key leadership tasks, managers also stay involved in model development and troubleshooting to maintain technical expertise. Effective communication and clear documentation are crucial, as remote teams rely on these to collaborate efficiently across different time zones. Balancing these responsibilities requires strong organizational skills and the ability to prioritize both people management and technical deliverables.
Manager Remote Machine Learning Engineer jobs near you
Infographic showing various Manager Remote Machine Learning Engineer job openings in Mantua, NJ as of June 2026, with employment types broken down into 86% Full Time, 10% Part Time, and 4% Contract. Highlights an 48% Physical, 3% Hybrid, and 49% Remote job distribution, with an average salary of $64,321 per year, or $30.9 per hour.

Data Scientist

Soni Resources

Conshohocken, PA • On-site, Remote

$175K/yr

Full-time

Re-posted 26 days ago

Job description

Data Scientist (Data Science + Data Engineering)
Location: Remote (Preference for Northeast/Mid-Atlantic; monthly travel to Plymouth Meeting, PA as needed)
Our client is building a data-driven culture where analytics, AI, and technology directly influence business decisions. They are seeking a Data Scientist who can translate complex business challenges into actionable insights while helping bring advanced analytics and machine learning solutions into production.
This role is ideal for someone who enjoys the full lifecycle of data science-from exploring data and building predictive models to partnering with engineering teams to deploy solutions that create measurable business value. The successful candidate will work closely with data engineers, business stakeholders, and executive leadership to help shape the future of analytics and AI across the organization.
While this is primarily a Data Science role, candidates should have a solid understanding of data engineering concepts and how models are operationalized within modern data ecosystems.
Responsibilities:
Data Science & Advanced Analytics
  • Analyze large and complex datasets to identify patterns, trends, and opportunities that support strategic business decisions.
  • Develop predictive models, scoring frameworks, and machine learning solutions that enhance business performance and decision-making.
  • Apply statistical and analytical techniques to solve real-world business problems and uncover actionable insights.
  • Continuously evaluate model effectiveness and recommend enhancements based on business outcomes and evolving data.
AI & Innovation
  • Contribute to the organization's growing AI strategy, including opportunities to leverage generative AI and emerging technologies.
  • Explore innovative approaches to automation, decision support, and workflow optimization through advanced analytics and AI solutions.
  • Partner with leadership to identify high-value use cases where AI can improve operational efficiency and decision quality.
Data Engineering Collaboration
  • Work closely with data engineering teams to ensure analytical solutions can be deployed, maintained, and scaled effectively.
  • Collaborate on the design and implementation of data pipelines that support machine learning and advanced analytics initiatives.
  • Help bridge the gap between model development and production deployment by ensuring solutions are practical, reliable, and business-ready.
  • Support efforts to improve data quality, accessibility, and governance across the organization.
Business Partnership
  • Engage directly with business stakeholders to understand challenges, define analytical approaches, and deliver impactful solutions.
  • Translate technical findings into clear, concise recommendations for both technical and non-technical audiences.
  • Serve as a trusted partner in helping business leaders make data-informed decisions.
Qualifications
Required
  • 3+ years of hands-on experience in Data Science, Analytics, Machine Learning, or a related quantitative field.
  • Proven experience developing predictive models or machine learning solutions in a business environment.
  • Strong proficiency in Python and modern data science libraries.
  • Advanced SQL skills and experience working with large-scale, complex datasets.
  • Experience applying statistical analysis and predictive modeling techniques to business problems.
  • Understanding of data engineering concepts, including data pipelines, model deployment, and production environments.
  • Experience working with cloud-based platforms such as Azure, AWS, or Google Cloud.
  • Strong communication and stakeholder management skills with the ability to explain technical concepts to business audiences.
Preferred
  • Experience collaborating closely with Data Engineering teams or supporting machine learning deployment initiatives.
  • Familiarity with distributed computing tools such as Spark or PySpark.
  • Experience developing AI-driven solutions, including Generative AI, Large Language Models (LLMs), or agent-based workflows.
  • Background in insurance, financial services, or other highly regulated industries.
  • Experience building production-grade machine learning applications.
  • Master's or PhD in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative discipline.

The ideal candidate:
  • Enjoys solving complex business problems through data.
  • Approaches challenges with curiosity and asks thoughtful questions.
  • Can balance analytical rigor with practical business impact.
  • Is comfortable working independently while collaborating across teams.
  • Takes ownership and drives projects from concept through implementation.
  • Learns new technologies and business domains quickly.
  • Values building solutions that can be used and adopted by the business-not just creating models.
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About Soni Resources

Sourced by ZipRecruiter

Soni is a premier staffing & recruitment company that is disrupting the human capital management space. Headquartered in New York, Soni has presence in 23 markets across the United States. We support each professional relationship with a cutting-edge approach, industry-leading insights, and a human touch. We are trusted to help companies and individuals tackle their challenges and capture their greatest opportunities. We are minority-owned, and diversity & inclusion is in our DNA. We are committed to creating environments where people are empowered to be their authentic selves.

Company size

11 - 50 Employees

Headquarters location

New York, NY, US

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