2

Remote Machine Learning Compiler Engineer Jobs in Norristown, PA

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 ...

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 ...

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 ...

Data Engineer

West Chester, PA · Remote

$108K - $130K/yr

Where You'll Work This role is remote; job seekers must reside in one of the following states to be ... Explore and learn about machine learning, data science, AI, and personalization technologies to ...

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.

... 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 ...

... 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 ...

Lead Data Scientist

Chadds Ford, PA · On-site +1

$144K - $250K/yr

Machine Learning * Python (Programming Language) * R Statistics * Statistical Analysis * Statistics ... Normal office environment. (Remote or Hybrid), 3 to 4 days per month are required in office if ...

Showing results 21-40

Remote Machine Learning Compiler Engineer information

See Norristown, PA salary details

$71.6K

$159.7K

$195.6K

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

As of Aug 9, 2026, the average yearly pay for remote machine learning compiler engineer in Norristown, PA is $159,747.00, according to ZipRecruiter salary data. Most workers in this role earn between $136,400.00 and $195,600.00 per year, depending on experience, location, and employer.

How does a remote machine learning compiler engineer typically collaborate with cross-functional teams to optimize model deployment?

As a Remote Machine Learning Compiler Engineer, you will frequently collaborate with data scientists, hardware engineers, and software developers to ensure that machine learning models are efficiently compiled and deployed on target platforms. Communication often takes place through virtual meetings, code reviews, and shared documentation tools. You'll be responsible for translating research models into optimized code, troubleshooting performance bottlenecks, and integrating feedback from various stakeholders. Effective teamwork is crucial, as the success of deployments often depends on iterative feedback and close alignment with both the ML research and hardware teams.

What is a remote machine learning compiler engineer?

A Remote Machine Learning Compiler Engineer is a software engineer who specializes in developing and optimizing compilers specifically for machine learning workloads, while working from a remote location. Their primary responsibilities include designing and implementing compiler features that translate machine learning models into efficient code for various hardware platforms, such as CPUs, GPUs, or specialized accelerators. They collaborate closely with machine learning researchers, hardware engineers, and software developers to ensure high performance and compatibility. In addition to strong programming skills, they typically require expertise in compiler theory, machine learning frameworks, and hardware architectures. This role allows for flexible, location-independent work while contributing to cutting-edge AI technologies.

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

AspectRemote Machine Learning Compiler EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Software Engineering, or related fields; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentPrimarily software development, compiler optimization, and ML model deploymentData analysis, model building, and interpretation of results
Industry UsageTech companies, AI startups, hardware firms focusing on ML hardware accelerationTech, finance, healthcare, and research organizations

While both roles involve working with machine learning, the Remote Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Remote Data Scientist concentrates on analyzing data and building predictive models. The roles share some technical skills but differ in their core responsibilities and work environments.

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

To thrive as a Remote Machine Learning Compiler Engineer, you need a strong background in computer science, proficiency in programming languages like C++ and Python, and expertise in compiler theory and machine learning frameworks. Familiarity with ML compilers such as TVM or XLA, and experience using version control and CI/CD systems are commonly required, along with a relevant bachelor's or master's degree. Outstanding problem-solving, collaboration, and communication skills are essential for working effectively in distributed teams and across technical domains. These skills and qualities enable the development of efficient, scalable ML solutions that bridge software and hardware, ensuring high performance and innovation.
What cities near Norristown, PA are hiring for Remote Machine Learning Compiler Engineer jobs? Cities near Norristown, PA with the most Remote Machine Learning Compiler Engineer job openings:

Principal Data Engineer - Safety Analytics (Global Medical Safety)

Johnson & Johnson

Horsham, PA • On-site, Remote

Full-time

Retirement, PTO

Re-posted 3 days ago


Johnson & Johnson rating

8.3

Company rating: 8.3 out of 10

Based on 112 frontline employees who took The Breakroom Quiz

25th of 86 rated pharmaceutical


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

What Johnson & Johnson employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom