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Manager Remote Machine Learning Engineer Jobs in Mantua, NJ

Abacum

AI Engineer

Barrington, NJ · Remote

Self-motivated with the ability to work independently in a fast-paced, remote-first environment ... Background in machine learning or predictive modeling to derive insights from large datasets.

TSMG

AI/ML Data Contributor

Philadelphia, PA · Remote

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

TSMG

AI/ML Data Contributor

Philadelphia, PA · Remote

... machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format, offering both remote and in-person opportunities (such as device ...

Bread Financial

Lead Data Scientist

Chadds Ford, PA · On-site +1

$144K - $250K/yr

Machine Learning * Python (Programming Language) * R Statistics * Statistical Analysis * Statistics ... Senior Manager and above Direct Reports : 0 Work Environment * Normal office environment. (Remote ...

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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.

Software Engineer (Full Stack)

Oncora Medical

Philadelphia, PA • On-site, Remote

$80/hr

Full-time

Medical, Dental, Retirement, PTO

Re-posted 25 days ago

Job description

Company Description
About us:
Oncora is an oncology software and data company dedicated to helping physicians and scientists collect and use real-world data to improve outcomes for cancer patients. Our machine learning algorithms, which are deployed in active clinical environments, accurately predict oncology outcomes such as unplanned hospitalization, survival, and recurrence. Our software products include: a clinical workflow and data entry system for oncology clinical care, a data warehouse that leverages connections to other healthcare software systems such as EMRs, PACS, to amass real-world, regulatory-grade oncology data, a machine learning platform to train and validate predictive models of key oncology events, a machine learning API to power external software tools, and a virtual clinical trial platform that allows pharma and device companies to leverage automated medical image analysis to advance new technologies in the fight to cure cancer. We work with world-leading cancer centers such as MD Anderson and Northwell Health, global device companies such as Varian Medical Systems, and innovative biopharma companies. Our team is mission-driven to its core.
Job Description
About the role:
We are looking for an experienced engineer to join our mission driven team to help develop our data platform that integrates and transforms multiple imperfect and messy data sources into clean, usable data so that we can learn from every cancer patient.
As a main contributor on our Platform and Integrations team, you will play a vital role in developing and operating our core data platform and helping scale it to serve additional hospitals.
We are a small team trying to tackle a very large problem, so we need teammates that are ultimately accountable to themselves and continuously push themselves, the product and the organization forward.
What you will be doing:
  • Gaining a deep understanding of oncology data and clinical workflows to be a better champion for our users
  • Working with product and engineering leadership to build a performant, user-friendly web application
  • Improving our frontend architecture as we expand our suite of products to meet a variety of clinical use cases
  • Adding new functionality to our GraphQL and REST APIs to support new product features
  • Instrumenting our API layer for metric collection, monitoring and alerting
  • Integrating the data generated by our data capture tool into our data platform and descriptive analytics product
  • Providing feedback (both design and code) to your peers

Qualifications
About you:
  • A solid base of software engineering experience, typically 1-5 years, in a modern single-page application environment
  • Fluency with the JavaScript / TypeScript ecosystem, modern frontend frameworks and build tools (we use React, Typescript, Webpack)
  • Strong foundation in programming, algorithms, and software application design
  • Tendency to seek simple, elegant solutions to complex problems
  • Ability to analyze and optimize existing solutions
  • Familitiary with various database technologies, including relational, document, key/value, columnar, etc (we use Postgres, Redis, MongoDB)
  • Experience with cloud computing providers (we use AWS)
  • Familiarity with modern containerized environments (we use Docker & Kubernetes)

Bonuses
  • Experience with healthcare data standards and integrations (HL7, FHIR, DICOM, etc.)
  • End-to-end experience working on greenfield products from inception to release
  • Experience with data visualization techniques and libraries

Additional Information
Compensation, Benefits, and Perks:
  • Salary: $80-120k plus equity compensation
  • 401k, health and dental insurance, flexible vacation policy, paid parental leave
  • eBooks, online courses, workstation setup
  • Events: happy hours, team dinners, conversations with oncologists (will return soon!)
  • You get to work with smart, passionate people on a product that will have a direct impact on the quality of life for cancer patients

What to expect in the hiring process:
  • Introductory phone call with the Head of Operations (30 minutes zoom call)
  • Phone interview with VP of Engineering (60 min zoom call)
  • A small take-home code challenge
  • Virtual onsite, including a technical discussion, engineering team meet, and co-founder meet (90-120 minute zoom call)
  • Final stages, potential follow-up interviews, and offer discussions

Sorry, we do not offer visa sponsorships at this time.
Oncora Medical is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, age, sex, religious creed, disability, ancestry, national origin, sexual orientation, gender identity, or gender expression

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