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About This Role
Location:
Wayne, PA, US, 19087
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Description:
IP Operations AI Intern
Hybrid (Remote Considered) \| Full\-Time Internship \| Wayne, PA
At Novocure, we're working to extend the lives of patients battling some of the most aggressive forms of cancer. As part of our Intellectual Property Operations team, you'll help develop and improve AI solutions that automate complex workflows, analyze data, and make information more accessible across the business.
This is a unique opportunity to apply cutting\-edge AI technologies to real\-world challenges in a highly collaborative environment. While you'll sit within the Intellectual Property organization, this is not a legal internship it's a technical role focused on AI development, automation, and intelligent systems.
ABOUT THE ROLE
We're looking for an AI\-focused intern who enjoys solving technical problems and building practical solutions. You'll partner directly with our Head of IP Operations to enhance existing AI agents, improve their reliability, and help create new automation tools that support business processes.
Rather than starting projects from scratch, you'll help evolve working AI systems by improving performance, strengthening safeguards, troubleshooting issues, and integrating enterprise data sources.
If you're excited about generative AI, LLMs, automation, APIs, and building intelligent systems that solve real business problems, we'd love to hear from you.
WHAT YOU’LL DO
Design Design, develop, and improve AI agents for document analysis, summarization, and data extraction
Enhance Retrieval\-Augmented Generation (RAG) workflows and improve AI accuracy and reliability
Refine prompts, system instructions, and agent logic to reduce hallucinations and improve performance
Integrate AI agents with enterprise applications, APIs, and internal databases
Troubleshoot AI workflows, identify bottlenecks, and improve system performance
Implement validation, security, and data privacy safeguards for enterprise AI applications
Collaborate on automation projects that improve operational efficiency across IP Operations
Document technical solutions, workflows, and recommendations for future development
Bring creative ideas and new approaches to emerging AI challenges
ABOUT YOU
You're curious, analytical, and enjoy figuring out why systems work—or why they don't. You're comfortable experimenting with new AI technologies and excited by opportunities to build practical solutions that have real business impact.
Minimum Qualifications
Currently pursuing a degree in Computer Science, Engineering, or related field
Rising junior or senior preferred
Strong programming skills in Python
Ability to work independently while collaborating with cross\-functional teams
Ability to commit to full\-time hours during the internship
Preferred Qualifications:
Experience working with Large Language Models (OpenAI, Gemini, Anthropic, or similar)
Familiarity with RAG architectures and AI agent frameworks such as LangChain, LlamaIndex, AutoGen, or similar
Experience working with APIs and structured data
Understanding of prompt engineering and AI evaluation techniques
Experience with software development, automation, or workflow tools
Familiarity with Airtable or similar low\-code platforms is a plus
No intellectual property or legal experience is required
WHAT SUCCESS LOOKS LIKE
Improved performance and reliability of existing AI agents
Successfully implemented AI solutions that integrate enterprise data
Helped build scalable automation capabilities within IP Operations
Demonstrated strong problem\-solving skills while troubleshooting AI systems
Contributed ideas that improve efficiency and support future AI initiatives
HOW YOU’LL WORK
Full\-time internship (approximately 8–10 weeks) with flexibility to continue part\-time during the academic year based on business needs and candidate availability
Remote\-friendly, with hybrid flexibility for candidates near Chesterbrook, PA
Direct mentorship from the Head of IP Operations
Collaborative environment with opportunities to contribute to AI initiatives across multiple business functions
WHAT YOU’LL GAIN
Paid Internship of $25/hr.
Hands\-on experience building real\-world AI systems
Exposure to cutting\-edge tools and frameworks in AI/ML
Opportunity to work on impactful projects in a regulated healthcare environment
Mentorship from experienced leaders in digital marketing and AI
ABOUT NOVOCURE:
Novocure is a company with a powerful mission, to extend the lives of people living with some of the most aggressive forms of cancer. Here your work will have a direct impact on patients and those who care about them. Join a team of passionate, collaborative people who support each other, challenge one another, and innovate together. Here, you’ll connect, grow, and make a real difference. We’re a company with the drive of a startup and the strength that comes with 25 years of success.
Novocure operates at a rare crossroad, where advanced medical technology converges with cutting\-edge biotechnology. We are the only company to develop and commercialize Tumor Treating Fields (TTFields), a proprietary, groundbreaking therapy designed to disrupt cancer cell division. With us you will find a unique combination of laboratory research work alongside engineering development of advanced technologies. This fusion of disciplines positions us as true pioneers in oncology innovation, leading a new frontier in the treatment of aggressive cancers.
Our patient\-forward values
– innovation
– focus
– drive
– courage
– trust
– empathy
\#LI\-RJ1
Novocure is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, 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 veteran and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.
Novocure is committed to providing an interview process that is inclusive of our applicant’s needs. If you are an individual with a disability and would like to request an accommodation, please email NovocureRecruitingEEO@novocure.com
If you're excited about this role, please apply.
Nearest Major Market: Philadelphia
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Novocure, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $120,000.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Novocure AI Hiring
Novocure has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Wayne, PA, US.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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