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Remote Machine Learning Engineer Jobs in Philadelphia, PA

Senior Software Engineer (Remote)

Philadelphia, PA · Remote

$123K - $163K/yr

This is a remote role anywhere in the USA. Meet the Team Our software engineering team develops ... Familiarity with LLMs, AI agents, embeddings, or other machine-learning capabilities and their ...

Our team offerings leverage advanced analytics, machine learning algorithms, and technology ... data scientists, developers, and clinical experts to translate clients' business needs into ...

Our team offerings leverage advanced analytics, machine learning algorithms, and technology ... data scientists, developers, and clinical experts to translate clients' business needs into ...

A.I. Manager

PA · On-site +1

Build and lead a remote AI team, including recruiting, mentoring, and performance management ... Guide model development, including machine learning, deep learning, NLP, and generative AI ...

Build and lead a remote AI team, including recruiting, mentoring, and performance management ... Guide model development, including machine learning, deep learning, NLP, and generative AI ...

Senior Staff AI/ML Engineer Job Category: Science Time Type: Full time Minimum Clearance Required ... S. in machine learning, computer science, mathematics, or related field 8+ years of AI/ML ...

Showing results 41-60

Remote Machine Learning Engineer information

See Philadelphia, PA salary details

$31.8K

$129.9K

$195.3K

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

As of Sep 12, 2026, the average yearly pay for remote machine learning engineer in Philadelphia, PA is $129,939.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,400.00 and $156,400.00 per year, depending on experience, location, and employer.

What is a remote machine learning engineer?

A Remote Machine Learning Engineer designs, develops, and deploys machine learning models while working from a remote location. They preprocess data, train and optimize models, and integrate them into production systems. Their role often involves collaborating with data scientists, software engineers, and stakeholders to solve complex problems using AI. Strong programming skills in Python, experience with ML frameworks like TensorFlow or PyTorch, and cloud computing knowledge are essential. Remote ML engineers must also communicate effectively and manage their time efficiently to work asynchronously with teams.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in computer science, mathematics, and experience with machine learning algorithms, typically supported by a relevant degree and prior project work. Proficiency with programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms is crucial, and certifications like AWS Certified Machine Learning can enhance your profile. Excellent communication, self-motivation, and time-management skills are also essential for collaborating across remote teams and meeting project goals. These combined technical and soft skills are vital for developing effective machine learning solutions while ensuring productivity and collaboration in a virtual work environment.

What are some typical challenges faced by remote machine learning engineers, and how are they addressed?

Remote Machine Learning Engineers often face challenges such as coordinating across different time zones, ensuring smooth communication with team members, and accessing large datasets or secure environments remotely. Organizations commonly address these by using robust collaboration tools (like Slack, GitHub, and Jira), establishing clear documentation, and setting regular virtual meetings to maintain alignment. Many companies also provide secure remote environments or VPN access for handling sensitive data and code. Proactive communication and organized workflows help mitigate these challenges, enabling engineers to remain productive and connected to their teams.

Are remote machine learning engineers still in demand?

Remote machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. Skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch are highly sought after, and many companies continue to hire for remote roles in this field.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for this role. The position typically involves tasks such as data analysis, model development, and collaboration through online tools, making remote work feasible with strong communication skills and proficiency in programming languages like Python or frameworks like TensorFlow. However, some roles may require occasional on-site meetings or access to specialized hardware.

What are the most commonly searched types of Machine Learning Engineer jobs in Philadelphia, PA?

The most popular types of Machine Learning Engineer jobs in Philadelphia, PA are:

What are popular job titles related to Remote Machine Learning Engineer jobs in Philadelphia, PA?

For Remote Machine Learning Engineer jobs in Philadelphia, PA, the most frequently searched job titles are:

What cities near Philadelphia, PA are hiring for Remote Machine Learning Engineer jobs?

Cities near Philadelphia, PA with the most Remote Machine Learning Engineer job openings:

Infographic showing various Remote Machine Learning Engineer job openings in Philadelphia, PA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $123,068 per year, or $59.2 per hour.

Principal Data Engineer - Safety Analytics (Global Medical Safety)

Titusville, NJ • On-site, Remote

Full-time

Retirement, PTO

Re-posted 6 days ago


Johnson & Johnson rating

8.3

Company rating: 8.3 out of 10

Based on 113 frontline employees who took The Breakroom Quiz


Job description

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions are personal.Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.Learn more at jnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Engineering

Job Category:

Scientific/Technology

All Job Posting Locations:

Horsham, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description:

About Innovative Medicine

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.
Learn more at https://www.jnj.com/innovative-medicine

Prefered Location:

Horsham, PA or Titusville, NJ. Remote work will considered on a case by case basis.

Role Overview

We are seeking a Principal Data Engineer to provide technical leadership within Global Medical Safety (GMS), supporting the Safety Analytics organization. This role is focused on building and enabling modern safety analytics tools using AI, Machine Learning, and GenAI, underpinned by robust, compliant, and scalable data engineering on Google Cloud Platform (GCP).

The Principal Data Engineer is responsible for end-to-end ownership of safety analytics data engineering, spanning data intake, data quality and continuity, pipeline and architecture design, automation, performance optimization, and compliance. The role enables advanced analytical, machine learning, and predictive capabilities for pharmacovigilance and serves as a technical data engineering leader within Global Medical Safety.

This is a Principal-level individual contributor role with broad technical influence, working closely with safety scientists, analytics teams, data scientists, IT, and platform partners to deliver trusted, production-grade analytics capabilities for safety decision-making.

Key Responsibilities

Safety Analytics & Pharmacovigilance Enablement

  • Design and maintain production-grade data pipelines and curated datasets that directly support pharmacovigilance activities, including safety monitoring, analytics, and regulatory reporting.

  • Ensure data engineering solutions produce reproducible, explainable, and trusted analytics outputs suitable for safety decision support and inspection readiness.

  • Enable AI/ML and GenAI workflows for safety analytics, including:

  • Feature engineering and feature store enablement
  • Embeddings, vectorized representations, and semantic retrieval
  • Retrieval-Augmented Generation (RAG) patterns for safety analytics tools

End-to-End Data Architecture & Lifecycle Ownership

  • Own the end-to-end data lifecycle for safety analytics, from source system intake through transformation, serving, and downstream analytical consumption, ensuring data continuity, traceability, and integrity.

  • Lead architectural decisions across ingestion, transformation, storage, and serving layers on GCP (e.g., BigQuery, Dataform, object storage).

  • Design, implement, and automate scalable, reusable data pipelines and architectures to support evolving safety analytics needs.

Data Quality, Governance & Compliance

  • Establish and enforce data quality, validation, lineage, and observability standards for safety analytics datasets.

  • Define and implement data governance practices, including data contracts, schema versioning, access control, stewardship, and lifecycle management.

  • Ensure safety analytics data and systems meet Global Medical Safety requirements for reliability, auditability, and regulatory use.

GxP Validation & Regulatory Readiness

  • Apply GxP validation expertise to data pipelines, analytics services, and supporting infrastructure.

  • Partner with quality and compliance teams to implement CSV/CSA-aligned controls, audit trails, documentation, and organizational change.

  • Balance delivery velocity and innovation with the rigor required for regulated pharmacovigilance systems.

Services, APIs & Microservices

  • Design and build APIs and microservices-based architectures to operationalize safety analytics and ML capabilities (e.g., feature serving, retrieval services, analytics backends).

  • Deploy and operate services on GCP (e.g., Cloud Run, GKE) with a strong focus on security, scalability, and observability.

  • Enforce contract-first integration patterns between producing and consuming systems to ensure reliability and safe evolution.

Infrastructure, CI/CD & Cost Optimization

  • Provision and manage cloud infrastructure using Terraform (Infrastructure as Code) on GCP.

  • Build and maintain CI/CD pipelines (e.g., Jenkins) for data pipelines, analytics services, feature pipelines, and ML data assets.

  • Continuously optimize the performance and cost efficiency of data and analytics infrastructure while maintaining compliance and reliability standards.

Technical Leadership & Stakeholder Engagement

  • Serve as a technical authority and data engineering leader for Safety Analytics within Global Medical Safety.

  • Review and influence designs across pipelines, services, feature stores, and AI/ML integrations to maintain a high technical bar. Collaborate closely with safety scientists, epidemiologists, biostatisticians, analytics teams, IT, and platform partners to translate safety needs into scalable technical solutions.

  • Communicate complex technical concepts and tradeoffs clearly to both technical and non-technical stakeholders.

  • Enable and upskill teams through mentorship, guidance, and knowledge sharing on modern data, cloud, and AI technologies.

Qualifications

  • Master's degree in Computer Science, Engineering, or a related field (or equivalent experience) is required.

  • 5+ years of experience in data engineering or analytics engineering with increasing responsibilities.

  • Proficient programming skills in Python and SQL.

  • Deep understanding of data architecture for analytics and ML (e.g., batch/streaming, modeling, performance optimization).

  • Proven ability to translate complex problems into clear, concise, and testable programming code/tools.

  • Experience implementing data contracts, data validation, schema versioning, and governance practices, as well as a solid understanding of leading cloud concepts (GCP preferred).

  • Experience designing and operating APIs and microservices-based architectures.

  • Excellent written and verbal communication, customer service, interpersonal, and teamwork skills to foster a collaborative team environment.

  • Solid understanding of SDLC and Agile methodologies, alongside basic project management skills.

  • Experience building production workloads on Google Cloud Platform (GCP) is preferred.

  • Experience provisioning infrastructure using Terraform (Infrastructure as Code) and building CI/CD pipelines (e.g., Jenkins) is preferred.

  • Experience in pharmaceuticals, life sciences, healthcare, or a related regulated domain is preferred.

  • GCP certification is preferred.

  • Experience enabling AI/ML and GenAI workflows (e.g., feature engineering, RAG patterns, semantic retrieval) for analytical applications is preferred.

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.


Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants' needs. If you are an individual with a disability and would like to request an accommodation, external applicants please
contact us via https://www.jnj.com/contact-us/careers , internal employees contact AskGS to be directed to your
accommodation resource.

#JNJTech

#LI-Hybrid

#LI-GR1

Required Skills:

Preferred Skills:

Advanced Analytics, Agility Jumps, Coaching, Critical Thinking, Data Engineering, Data Governance, Data Modeling, Data Privacy Standards, Data Science, Digital Fluency, Execution Focus, Hybrid Clouds, Organizing, Presentation Design, Technical Development, Technical Writing, Technologically Savvy

The anticipated base pay range for this position is :

$102,000.00 - $177,100.00

Additional Description for Pay Transparency:

Subject to the terms of their respective plans, employees are eligible to participate in the Company's
consolidated retirement plan (pension) and savings plan (401(k)).
Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:
Vacation -120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado -48 hours per calendar year; for employees who reside in the State of Washington -56 hours per calendar year
Holiday pay, including Floating Holidays -13 days per calendar year
Work, Personal and Family Time - up to 40 hours per calendar year
Parental Leave - 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave - 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
Caregiver Leave - 80 hours in a 52-week rolling period10 days
Volunteer Leave - 32 hours per calendar year
Military Spouse Time-Off - 80 hours per calendar year
For additional general information on Company benefits, please go to: - https://www.careers.jnj.com/employee-benefits

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