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Tensorflow Pytorch Jobs in Garner, NC (NOW HIRING)

Senior AI Performance Architect

Raleigh, NC · On-site

$162K/yr

Knowledge of front-end ML frameworks (i.e.,TensorFlow, PyTorch) used for training of ML models * Strong communication skills (written and verbal) * Detail-oriented with strong problem-solving ...

Senior Systems Engineer

Raleigh, NC · On-site +1

$101K - $139K/yr

... MLflow, TensorFlow/PyTorch, LangChain, LlamaIndex at a conceptual level). Consulting Skills • Skilled at asking the right questions to uncover technical requirements, constraints, and business ...

Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn Required Skills * Experience ...

Lead AI / ML Engineer

Raleigh, NC · On-site

$99K - $131K/yr

Familiarity with AI and machine learning frameworks (e.g., TensorFlow, PyTorch). Experience on big data technologies and tools (e.g., Hadoop, Spark). * Database management and data processing.

New

Required : • Expertise in Python (including NumPy, pandas, and other packages) • Experience with either PyTorch or TensorFlow • Deep understanding of machine learning fundamentals (gradient ...

Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience translating research ideas into production systems. Preferred Qualifications: * Deep experience with ...

Showing results 21-40

Tensorflow Pytorch information

See Garner, NC salary details

$33.4K

$109.4K

$175.2K

How much do tensorflow pytorch jobs pay per year?

As of Aug 8, 2026, the average yearly pay for tensorflow pytorch in Garner, NC is $109,406.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,800.00 and $121,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a deep learning engineer specializing in TensorFlow and PyTorch?

To thrive as a Deep Learning Engineer with a focus on TensorFlow and PyTorch, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant degree. Proficiency in programming languages like Python, experience with TensorFlow and PyTorch frameworks, and familiarity with cloud platforms or GPU computing are essential. Analytical thinking, problem-solving, and effective communication are standout soft skills for collaborating with teams and interpreting model results. These skills are crucial for developing, deploying, and optimizing AI models that drive innovation and solve complex real-world problems.

What are TensorFlow and PyTorch?

TensorFlow and PyTorch are two of the most popular open-source deep learning frameworks used by researchers and developers to build, train, and deploy machine learning models. TensorFlow, developed by Google, offers robust support for production environments and has a large ecosystem. PyTorch, developed by Facebook, is known for its flexibility, ease of use, and dynamic computational graph, making it popular in academia and research. Both frameworks support a wide range of neural network architectures and are used extensively for tasks such as computer vision, natural language processing, and reinforcement learning.

What is the difference between Tensorflow Pytorch vs Data Scientist?

AspectTensorflow PytorchData Scientist
Required SkillsDeep learning frameworks, Python, machine learningData analysis, statistical skills, Python/R, machine learning
Work EnvironmentAI/ML development, research, software engineeringData analysis, reporting, business insights
Industry UsageAI/ML projects, research labs, tech companiesBusiness, finance, healthcare, tech

Tensorflow and Pytorch are deep learning frameworks used primarily by AI/ML developers, while Data Scientists utilize these tools for data analysis and modeling. Although their skill sets overlap, Tensorflow Pytorch focus on model development, whereas Data Scientists apply these models to derive insights and inform decisions.

How do TensorFlow/PyTorch engineers typically collaborate with data scientists and other team members in a production environment?

TensorFlow and PyTorch engineers often work closely with data scientists to transform experimental machine learning models into efficient, scalable production solutions. Collaboration involves frequent code reviews, shared development environments, and regular meetings to align model requirements with deployment constraints. Engineers also coordinate with DevOps teams to ensure smooth integration and monitoring of models in production. Strong communication skills and a willingness to iterate on solutions are essential for bridging the gap between research and real-world application.
What job categories do people searching Tensorflow Pytorch jobs in Garner, NC look for? The top searched job categories for Tensorflow Pytorch jobs in Garner, NC are:
What cities near Garner, NC are hiring for Tensorflow Pytorch jobs? Cities near Garner, NC with the most Tensorflow Pytorch job openings:

Lead AI Engineer, Biomedical & Vigilance Innovation Software

Front Door Defense

Durham, NC • On-site

$120 - $160/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 3 days ago

New


Job description

Lead AI Engineer, Biomedical & Vigilance Innovation Own and drive the development of production-grade AI platforms for pharmacovigilance and safety signal detection

Location: North Carolina, United States

About The Role

United Therapeutics is a biopharma company focusing on rare and cutting‑edge therapies.

We are seeking a Lead AI Engineer with a start‑up mindset to design, develop, and deploy advanced AI solutions that transform how biomedical insights are generated and how safety signals are detected, assessed, and acted upon. The role operates at the intersection of data science, software engineering, and medical safety, applying advanced analytics, machine learning, and automation to create scalable platforms that support proactive risk management and accelerate informed decision‑making across the product lifecycle.

Key Responsibilities
  • Design, build, validate, and maintain machine learning, natural language processing, and generative AI solutions for biomedical and pharmacovigilance use cases.
  • Develop tools that support adverse event intake, case triage, coding assistance, duplicate detection, signal prioritization, and trend analysis.
  • Engineer predictive models to identify emerging risks, patient patterns, and operational bottlenecks.
  • Translate complex scientific and business requirements into production‑ready AI applications.
  • Own model definition, fine‑tuning, and optimization to ensure fit‑for‑purpose AI solutions for the UT patient safety business.
  • Define and execute a bold technology strategy spanning global patient safety, embedding AI, machine learning, and agentic automation across day‑to‑day PV operations, analytics, and signal detection.
  • Drive the architecture, development, and delivery of next‑generation platforms for pharmacovigilance AI initiatives.
  • Integrate structured and unstructured data from safety databases, clinical systems, literature, real‑world evidence, and external repositories.
  • Create staging schemas and mine diverse sources for hidden trends and meaningful insights.
  • Build scalable pipelines for data ingestion, transformation, and quality control.
  • Apply ontology mapping, terminology harmonization, and metadata strategies across MedDRA, WHO Drug, and related standards.
  • Ensure robust data lineage, traceability, and audit readiness.
  • Support modernization of pharmacovigilance and organovigilance systems through AI‑enabled automation and decision support tools.
  • Improve case processing efficiency, medical review, and governance reporting via AI‑enabled solutions.
  • Contribute to next‑generation surveillance models for novel modalities such as xenotransplantation, cell therapy, gene therapy, and organ‑based therapeutics.
  • Develop AI‑enabled dashboards and visualization tools for rapid interpretation of safety trends.
  • Ensure AI models and digital tools align with GxP, privacy, security, validation, and regulatory expectations.
  • Support model governance including performance monitoring, unbiased detection, explainability (XAI), and change control.
  • Maintain documentation for validation, testing, intended use, and lifecycle management.
  • Collaborate with safety, clinical, regulatory, medical affairs, biostatistics, and IT teams.
  • Provide technical guidance to analysts, data scientists, and business partners.
  • Deliver validated AI solutions that create measurable gains in vigilance quality, speed, and insight generation.
  • Improve detection and prioritization of safety signals through advanced analytics.
  • Enhance case processing and review efficiency while preserving quality and compliance.
  • Establish reliable, scalable biomedical data assets for future innovation.
  • Maintain regulatory‑ready governance for AI‑enabled safety systems.
  • Advance our leadership position in responsible AI for the future of medicine.
  • Perform other duties as required.
Minimum Requirements
  • Bachelor’s, Master’s, or PhD in computer science, engineering, applied mathematics, data science, biomedical engineering, bioinformatics, artificial intelligence, or related field, with the following experience: 8+ years with a Bachelor’s, 6+ years with a Master’s, or 2+ years post‑PhD.
  • 5+ years of experience in AI engineering, machine learning, or advanced analytics within biopharma, healthcare, or regulated industries.
  • 5+ years of hands‑on expertise in AI tools such as Python, R, MATLAB, TensorFlow, PyTorch, and cloud‑based ML platforms.
  • Track record of deploying AI, machine learning, and data science solutions that deliver measurable outcomes in production environments.
  • Entrepreneurial, transformation‑oriented mindset able to move from concept to execution quickly and lead technology‑driven change.
  • Background in AI‑native product development, including agentic AI, LLM‑powered applications, autonomous systems, computer vision, or ML‑driven process optimization.
  • Strong problem‑solving capability and ability to operate in complex matrixed environments.
  • Deep fluency in cloud‑native engineering, platform architecture, and modern software development practices.
  • Experience with external innovation strategies, academic partnerships, and emerging technology investments.
  • Engineering mindset to build production‑grade, compliant, and scalable platforms, not just proof‑of‑concept demos.
  • Excellent communication skills for conveying technical outputs to non‑technical stakeholders and senior leadership.
  • Ability to learn scientific domains quickly and ask insightful questions to drive technology improvements in manufacturing timelines, quality, and cost.
Preferred Qualifications
  • 5+ years of experience with NLP, LLMs, knowledge graphs, or biomedical text mining.
  • Experience with safety systems such as Argus, ArisG, Veeva, or equivalent platforms.
  • Knowledge of pharmacovigilance, clinical development, biomedical data, or healthcare regulations.
  • Exposure to drugs, biologics, devices in the rare disease space or advanced therapeutics.
  • Curiosity about and willingness to develop deep domain expertise in pharma automation workflows, advanced analytics, and risk‑identification methodologies.
  • Hands‑on experience with pharmacokinetic (PK) / pharmacodynamic (PD) modeling and simulation applied to AI in pharmacovigilance.
  • Familiarity with GVP, FDA, EMA, ICH, and data privacy frameworks.
Benefits

This position will be located at our Durham, NC office with a hybrid schedule of 4 days in office and the option to work 1 day each week from home. Eligible employees may participate in the Company’s comprehensive benefits suite, including medical, dental, vision, prescription coverage, employee wellness resources, savings plans (401k, ESPP), paid time off, paid parental leave, disability benefits, and more.

Equal Opportunity Employer

United Therapeutics Corporation is an Equal Opportunity Employer, including veterans and individuals with disabilities. We strive to engage the minds, hearts, and most spirited efforts of each employee. This is a stimulating place to work.

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