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Intern Vector Jobs in California (NOW HIRING)

Nokia

AI R&D Engineer Co-op

Sunnyvale, CA · Hybrid

$20.10 - $70.40/hr

Search engines and vector databases, along with their underlying algorithms. * Big data frameworks ... Experience level Student or Intern or Trainee * Locations 520 Almanor Avenue, Sunnyvale, California ...

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Intern Vector information

What typical projects or tasks can an Intern Vector expect to work on during their internship?

As an Intern Vector, you can expect to support projects involving data analysis, algorithm development, and software testing, often under the guidance of senior engineers or data scientists. Your daily responsibilities may include assisting with coding, debugging, and documentation, as well as collaborating with team members during meetings or code reviews. This role provides valuable exposure to real-world technical challenges and the opportunity to contribute to meaningful projects, helping you build practical skills and professional relationships that can aid in your future career growth.

What is the difference between Intern Vector vs Intern Data Analyst?

AspectIntern VectorIntern Data Analyst
Required CredentialsBasic coursework in vector mathematics, computer science, or related fieldsCoursework in statistics, data analysis, or related fields
Work EnvironmentTech companies, research labs, or software development teamsBusiness, finance, healthcare, or marketing departments
Employer & Industry UsageUsed in fields involving computer graphics, simulations, or machine learningCommon in industries analyzing data for insights and decision-making
Search & Comparison IntentUnderstanding roles involving vector computations or graphicsRoles focused on data analysis and interpretation

Intern Vector typically involves working with mathematical vectors in tech or research settings, focusing on algorithms or graphics. Intern Data Analyst centers on analyzing data sets to generate insights, often in business or healthcare. While both are internships, their focus areas and skill requirements differ significantly, catering to distinct industry needs.

What are Intern Vectors?

Intern Vector positions are typically internship roles focused on vector mathematics, data structures, or computational tasks involving vectors, often in fields like computer science, data analysis, or engineering. Interns in these roles may assist with coding, machine learning projects, or research that involves vector operations and algorithms. These internships provide hands-on experience, mentorship, and a chance to develop technical skills relevant to the industry. Intern Vectors help bridge academic knowledge with real-world applications, giving students a valuable entry point into their chosen fields.

What are the key skills and qualifications needed to thrive as an Intern Vector, and why are they important?

To thrive as an Intern Vector, you typically need a background in mathematics, computer science, or engineering, supported by ongoing pursuit of a relevant degree. Familiarity with programming languages (such as Python or C++), data analysis tools, and version control systems like Git is often expected. Strong communication, teamwork, and adaptability help you integrate into professional environments and contribute effectively to projects. These skills and qualities are crucial for successfully applying academic knowledge in practical settings and for building a foundation for future career growth.
What are the most commonly searched types of Vector jobs in California? The most popular types of Vector jobs in California are:
What are popular job titles related to Intern Vector jobs in California? For Intern Vector jobs in California, the most frequently searched job titles are:
What job categories do people searching Intern Vector jobs in California look for? The top searched job categories for Intern Vector jobs in California are:
What cities in California are hiring for Intern Vector jobs? Cities in California with the most Intern Vector job openings:
Intern Vector jobs near you
AI/Machine Learning Engineering - Intern

AI/Machine Learning Engineering - Intern

DataVisor

Mountain View, CA • On-site

$25 - $70/hr

Full-time, Internship

Posted 23 days ago

Job description

About DataVisor

DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Role Summary

We are seeking highly motivated, soon-to-graduate MS or Ph.D. students in Computer Science, Machine Learning, Data Science, or related fields to join us as AI / ML Engineering Interns.

This internship is ideal for candidates who are eager to learn how large-scale AI systems are built and deployed in production. You will work closely with experienced engineers and data scientists to help build the Intelligence Layer and Data Consortium that power DataVisor’s real-time fraud detection platform.

This internship focuses on distributed systems, data pipelines, machine learning infrastructure, and applied AI, including exposure to agentic flows and large language models (LLMs).

What You’ll Do

  • Data Engineering & Pipelines
    • Assist in building and maintaining high-throughput data pipelines using technologies such as Spark, Kafka, or Flink
    • Help process and aggregate real-time signals (e.g., device fingerprints, behavioral data) into shared intelligence systems
  • Distributed Systems & Scalability
    • Learn to design and optimize backend systems that support large-scale, real-time decisioning
    • Contribute to improving system performance, reliability, and latency under high transaction volumes
  • AI Applications & Agentic Flows
    • Support the development of AI applications and agentic workflows using state-of-the-art LLMs (e.g., OpenAI, Anthropic, Google)
    • Experiment with natural language interfaces, intelligent rule suggestions, and automated strategy generation
  • Machine Learning Pipelines
    • Help deploy and monitor pipelines for unsupervised and supervised ML models
    • Assist with integrating models into real-time scoring APIs and decision engines
  • Privacy & Security
    • Learn best practices for privacy-first system design, including tokenization and hashing to protect sensitive data
  • Cross-Functional Collaboration
    • Work alongside Data Science, Product, and Engineering teams to test ideas, validate models, and ship production features

Requirements

  • Current MS or Ph.D. students majoring in Computer Science, Machine Learning, AI, Data Science, or a related field
  • Passionate about learning how real-world AI systems are built at scale
  • Comfortable working with complex technical problems and eager to grow through mentorship
  • Strong programming skills in Python
  • Familiarity with at least one of the following: distributed systems, machine learning, data engineering, or backend development
  • Academic or project experience with big data frameworks (Spark, Kafka, Flink) is a plus
  • Understanding of core ML concepts (supervised / unsupervised learning)
Preferred (Nice-to-Have)
  • Coursework or project experience with:
    • LLMs, RAG architectures, LangChain, or vector databases
    • Cloud platforms (AWS) and containers (Docker)
    • Stream processing or real-time systems
  • Interest in fraud, risk, or security domains (not required)

Benefits

  • Hands-on experience working on production-scale AI systems
  • Mentorship from senior engineers and data scientists
  • Exposure to cutting-edge agentic AI and LLM applications
  • Opportunity for full-time conversion based on performance and business needs
  • Comp Range, $25 - $70/hour