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Manager Remote Machine Learning Engineer Jobs in Mantua, NJ

KPMG

Director, AI Engineer

Philadelphia, PA · On-site +1

Manage and mentor cross-functional teams, promoting a high-performance culture, technical ... Professional AI Architect, Machine Learning Engineer) or equivalent are a plus * Advanced degree ...

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 ...

Mondo

Technical Product Manager

Talleyville, DE · Remote

$80 - $90/hr

Remote (East Coast candidates preferred) Start Date: ASAP Duration: 6-12 Month Contract ... Partner with engineering managers and tech leads to shape, document, and refine technical ...

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.

Pepperidge Farm, Incorporated

Data Scientist

Camden, NJ · On-site +1

$109K - $150K/yr

You will leverage machine learning and advanced analytics to improve forecast accuracy, optimize ... Use the o9 platform and open-source IDEs for model development, deployment, data management, and ...

Campbell's

Data Scientist

Camden, NJ · On-site +1

$109K - $150K/yr

You will leverage machine learning and advanced analytics to improve forecast accuracy, optimize ... Use the o9 platform and open-source IDEs for model development, deployment, data management, and ...

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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 Jul 17, 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
Software Engineer (Platform)

Software Engineer (Platform)

Oncora Medical

Philadelphia, PA • Remote

$80/hr

Full-time

Medical, Dental, Retirement, PTO

Re-posted 4 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:

  • Developing pipelines to integrate new data elements into our normalized oncology schema
  • Overseeing and monitoring our existing data infrastructure for stability, performance and accuracy
  • Improving our data warehousing and reporting capabilities to support real-time analysis of tens of thousands of patients representing millions of data points
  • Integrating standard and proprietary ontologies into our data enrichment processes
  • Enhancing our de-identification capabilities to support machine learning and clinical research use-cases 
  • Building reusable integrations with major clinical systems (e.g. EMR/EHRs)
  • Deploying updates frequently to immediately improve the state of cancer care
  • Providing constructive feedback to your team members through code and architecture reviews
Qualifications

About you:

  • A solid base of software engineering experience, typically 1-5 years, with at least part of that time in data-focused roles or projects
  • Fluency with a functional or imperative language (we use Python)
  • Experience working with relational and non-relational databases (we use Postgres, MongoDB, Redis, and ElasticSearch)
  • Tendency to seek simple, elegant solutions to complex problems
  • Ability to analyze and optimize existing solutions
  • A focus on writing understandable, testable, and maintainable code
  • Experience working with asynchronous and distributed systems (we use RabbitMQ)
  • Familiarity with modern containerized environments (we use Docker & Kubernetes)

Bonuses: 

  • Experience with healthcare data standards and integration is a huge plus (HL7, FHIR, DICOM, etc.)
  • Experience designing data models for analytical and transactional workloads
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)
  • Virtual onsite, including a pair programming session, engineering team meet, and co-founder meet (90-120 minute zoom call)
  • Final stages, potential follow-up interviews, and offer discussions

Apply