AI/ML Engineering Intern developing large-scale AI systems at DataVisor for real-time fraud detection. Collaborating with experienced engineers and data scientists to build AI applications and data pipelines.
Responsibilities
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
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
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
Help deploy and monitor pipelines for unsupervised and supervised ML models
Assist with integrating models into real-time scoring APIs and decision engines
Learn best practices for privacy-first system design, including tokenization and hashing to protect sensitive data
Work alongside Data Science, Product, and Engineering teams to test ideas, validate models, and ship production features
Requirements
Recently graduated or currently completing an MS or Ph.D. 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
Job title
AI/Machine Learning Engineering Intern, MS/Ph.D. New Grad
Trainer at WeAndTheMany facilitating learning by sharing experiences and creating interactive sessions. Engaging with students to enhance their skills and knowledge through dynamic teaching methods.
Machine Learning Manager leading experienced team to drive data - driven AI/ML solutions at Ford. Overseeing strategies for product development focused on analytics in various domains.
Software Engineer I developing machine learning models and applications at Smart Data Solutions. Collaborating to improve infrastructure and automate processes using AI technology.
Intermediate Machine Learning Engineer at Aviva Canada implementing ML pipelines with required collaboration in AI/ML Operations. Join a team dedicated to operationalizing ML models for optimizing solutions.
MLOps Engineer designing and maintaining cloud infrastructure for large - scale computer vision model training. Collaborating with Data Scientists and AI Engineers to streamline model development lifecycle.
Machine Learning Engineer developing AI - first dating solutions at Hinge, enhancing user matchmaking and conversation experience. Collaborating with cross - functional teams to move ML models to production.
Senior ML Engineer designing and developing machine learning models for national security. Collaborating with cross - functional teams to deliver scalable solutions in defense applications.
Machine Learning Engineer developing and deploying ML planning algorithms for autonomous trucks. Join Plus, a leader in AI - based virtual driver software for autonomous trucking.
Intern for Servo Engineering at Seagate, integrating AI/ML into precision servo design. Collaborating on research and optimization of control algorithms for hard disk systems.
Intern role focused on Machine Learning and Generative AI projects for Seagate's innovative data solutions. Contributing to precision - engineered storage initiatives in Singapore.