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Pytorch Developer Jobs in Pennsylvania (NOW HIRING)

ML Engineer

Malvern, PA · On-site

$100K - $135K/yr

... PyTorch. • AWS Cloud Services Proficiency in S3, EC2, IAM, Lambda, ECR, ECS/EKS, CloudWatch, and ... Roles & Responsibilities Senior AWS ML Engineer with 8+ years of experience in • Design, build ...

... PyTorch Mobile) * Familiarity with Distributed Deep Learning (DDL) techniques and frameworks ... Experience with DevOps practices such as CI/CD automation, containerization (Docker, Kubernetes ...

Research Engineer

Pittsburgh, PA · On-site

$100K - $300K/yr

Position Overview We are hiring Research Engineers to develop scalable robotic systems aimed at ... Proficiency in Python and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.

Generative AI Data Engineer III

Philadelphia, PA · On-site

$115K - $138K/yr

Our Deloitte AI & Engineering team works to transform technology platforms, drive innovation, and ... Active Certification/Advanced certification in Python, Pyspark, Pytorch, Tensorflow * Ability to ...

Research Engineer

Pittsburgh, PA · On-site

$100K - $300K/yr

Position Overview We are hiring Research Engineers to develop scalable robotic systems aimed at ... Proficiency in Python and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.

Showing results 21-40

Pytorch Developer information

What is a PyTorch developer?

A PyTorch Developer is a software engineer or data scientist who specializes in using PyTorch, an open-source machine learning library, to build and deploy deep learning models. Their responsibilities typically include designing neural network architectures, training and evaluating models, and optimizing code for performance. PyTorch Developers work in fields such as artificial intelligence, computer vision, and natural language processing, collaborating with teams to solve complex problems using machine learning. They are proficient in Python and have a strong understanding of deep learning concepts. Additionally, they often contribute to research, development, and the deployment of AI solutions in production environments.

What are some common challenges PyTorch developers face when deploying machine learning models to production environments?

Pytorch Developers often encounter challenges when transitioning models from research to production, such as optimizing model performance for inference speed and memory usage, ensuring compatibility with deployment frameworks like TorchScript or ONNX, and managing dependencies across different systems. Additionally, integrating PyTorch models into existing software stacks and maintaining reproducibility can be complex. Collaborating closely with DevOps and data engineering teams is crucial to address these issues and ensure smooth deployment.

What are the key skills and qualifications needed to thrive as a PyTorch developer, and why are they important?

To thrive as a Pytorch Developer, you need strong programming skills in Python, a solid grasp of machine learning concepts, and experience with deep learning frameworks—especially PyTorch itself. Familiarity with tools like CUDA, Jupyter Notebooks, and version control systems (e.g., Git) is typically expected, along with knowledge of cloud platforms or relevant certifications. Problem-solving ability, effective collaboration, and clear communication are crucial soft skills for success in this role. These skills and qualities are vital for efficiently building, optimizing, and deploying machine learning models in real-world applications.

What is the difference between Pytorch Developer vs Machine Learning Engineer?

AspectPytorch DeveloperMachine Learning Engineer
Required CredentialsBachelor's or higher in CS, experience with PyTorchBachelor's or higher in CS, data science, or related field, with ML experience
Work EnvironmentResearch labs, AI startups, tech companies focusing on deep learningTech companies, finance, healthcare, often involving deployment and scaling ML models
Industry UsagePrimarily in AI research and development teamsAcross industries implementing ML solutions in production

While both roles require knowledge of machine learning and experience with PyTorch, a Pytorch Developer mainly focuses on developing and optimizing deep learning models using PyTorch. A Machine Learning Engineer often has a broader scope, including deploying, maintaining, and scaling ML models across various platforms and industries.

What cities in Pennsylvania are hiring for Pytorch Developer jobs?

Cities in Pennsylvania with the most Pytorch Developer job openings:

Infographic showing various Pytorch Developer job openings in Pennsylvania as of August 2026, with employment types broken down into 77% Full Time, 10% Part Time, and 13% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution.

ATAK Developer - Clearance Required

LMI Consulting, LLC

Pittsburgh, PA • On-site

Other

Posted 18 days ago


Job description

ATAK Developer - Clearance Required
Job Locations US-Remote | US-PA-Pittsburgh
ID 2026-14304 # of Openings 1
Overview

LMI is seeking a skilled ATAK Plugin Developer to support the design, development, and deployment of mission-critical plugins for the Android Tactical Assault Kit (ATAK). This role focuses on designing cutting-edge ATAK plugins and systems capable of operating at the tactical edge while enabling seamless integration with broader military systems, creating solutions to support military operations, situational awareness, and real-time decision-making. This position offers the opportunity to innovate at the intersection of software development, edge computing, and tactical applications. Candidates must be self-motivated, collaborative, and comfortable working in fast-paced, mission-oriented environments with a focus on operating in contested and resource-constrained environments.

LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.

Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors-helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

Responsibilities
    Design, develop, and deliver custom ATAK plugins that enhance field-deployable tactical applications in disconnected, contested, or low-bandwidth environments
  • Leverage advanced techniques to enable Edge MLOps workflows and support distributed, on-device machine learning (ML) for real-time decision support and situational awareness
  • Work with geospatial data, real-time location services, and operational overlays to improve mapping and data visualization capabilities within ATAK
  • Support and extend functionality for TAK Server integration and ensure seamless data exchange between mobile applications and central server components
  • Optimize software to ensure efficient performance on low-resource devices in harsh or contested environments
  • Implement and maintain robust and secure API-based integrations (REST, WebSocket, gRPC, or similar) to support real-time collaboration and data sharing
  • Troubleshoot complex integration challenges, including data synchronization in environments with intermittent or limited connectivity
  • Ensure plugins align with military cybersecurity and STIG compliance requirements, providing DoD-compliant solutions
  • Document technical designs, workflows, and processes to ensure replicable, high-quality development and deployment efforts
  • Collaborate with multi-disciplinary teams, including software engineers, data scientists, and military stakeholders, to define and refine requirements

Percentage of Travel Required: Up to 10%

Qualifications
Minimum Qualifications:
  • 3-5 years of software development experience, including mobile applications, plugin development, or backend systems
  • 2+ years of experience developing for Android platforms (using Kotlin and/or Java)
  • Familiarity with edge computing concepts, including resource optimization on low-powered devices and intermittent or contested network environments
  • Proficiency in API integration and building highly-performant, secure software architectures
  • Understanding of military systems, particularly related to aTAK/Tactical Assault Kits
  • Knowledge of system security, particularly DoD cybersecurity guidelines and frameworks (e.g., STIGs, RMF compliance)
  • Strong debugging, troubleshooting, and performance optimization skills for distributed systems and mobile apps
  • Ability to work independently as well as collaboratively within multi-disciplinary teams
  • Active Secret clearance (or ability to obtain one)

Preferred Qualifications:

  • Experience implementing machine learning models for edge devices (e.g., TensorFlow Lite, ONNX Runtime, or PyTorch Mobile)
  • Familiarity with Distributed Deep Learning (DDL) techniques and frameworks optimized for edge networks or contested environments
  • Understanding of MLOps pipelines for deploying, monitoring, and retraining models at scale on decentralized systems
  • Strong understanding of DoD cybersecurity standards and best practices, particularly surrounding STIG requirements and RMF processes
  • Experience hardening applications and infrastructure for deployment in classified environments or contested tactical settings
  • Familiarity with accompanying web applications (e.g., mission command dashboards or admin portals) to visualize and manage analytics, location, or operational data
  • Skills in modern frontend frameworks (React, Angular, Vue) and backend/API development in frameworks like Flask, Django, or FastAPI
  • Experience with geospatial software and tools, including GIS standards and libraries such as GDAL, GeoServer, or Mapbox
  • Familiarity with TAK Server configurations, architectures, and plugins
  • Background working in defense/DoD environments or direct experience supporting military operations
  • Knowledge of tactical data link protocols (e.g., Link 16) and secure communication standards
  • Strong scripting abilities in Python, Bash, or similar languages
  • Demonstrated ability to communicate complex technical concepts effectively to non-technical stakeholders or military leadership
  • Experience with DevOps practices such as CI/CD automation, containerization (Docker, Kubernetes), and cloud deployments (AWS, Azure, GCP)

Target salary range: $110,000 - 160,000

Disclaimer: The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.

Applicants must meet eligibility requirements for a U.S. Government security clearance. Only US Citizens are eligible for a security clearance. For this position, LMI will only consider applicants with security clearances or applicants who are eligible for security clearances, due to the nature of the work.

Job Locations
US-Remote
US-PA-Pittsburgh

LMI is an Equal Opportunity Employer. LMI is committed to the fair treatment of all and to our policy of providing applicants and employees with equal employment opportunities. LMI recruits, hires, trains, and promotes people without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy, disability, age, protected veteran status, citizenship status, genetic information, or any other characteristic protected by applicable federal, state, or local law. If you are a person with a disability needing assistance with the application process, please contact accommodations@lmi.org
Colorado Residents: In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.
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