AI Internship

Position Level: Internship – Part-Time
Location: Remote, No Travel
Department: Software Engineering
Duration: 3-6 Months
Reports to: Managing Director
Application Deadline: August 22, 2025

Company Overview

Quantisage is “Where Growth Meets Compliance” consulting firm on a mission to provide Customers with the world’s leading technology and compliance solutions while promoting the well-being and development of our associates and partners.

Quantisage is strongly committed to the influence of AI in the Commercial and Public Sectors. Quantisage is at the forefront of developing cutting-edge AI solutions. Our platform transforms raw operational data into actionable intelligence, helping executives make strategic and tactical decisions across critical business functions. We’re focused on solving complex business challenges through advanced AI technologies.

Job Overview

Job Title: AI Intern- Part Time
Location and Residency Status: Remote
Time Commitment Expectation: 15-20 Hrs Weekly

We’re seeking a technically proficient AI/ML Engineering Intern to contribute directly to the development and deployment of our AI-based products. This is a hands-on technical role where you’ll work with our core AI/ML stack, implementing models and infrastructure that solve complex business challenges. There is a possibility of converting this roles from Internship to Employment after 3 Months based on the Performance.

Duties & Responsibilities

Responsibilities

• Build and optimize machine learning models for our four core use cases using Python and frameworks like scikit-learn, TensorFlow, PyTorch, and XGBoost
• Design and implement data processing pipelines using Apache Airflow and Kafka
• Work with data lakes (S3/ADLS) and data warehouses (Snowflake/BigQuery)
• Develop ETL/ELT processes for both batch and real-time data ingestion
• Containerize models using Docker and deploy to Kubernetes clusters
• Implement model serving using FastAPI and MLflow
• Contribute to knowledge graph development using Neo4j or Tiger Graphs
• Develop monitoring solutions using Prometheus, Grafana, and ELK stack

Experience building UI/UX using Reactjs, and other technologies

Educational Qualifications

Required Qualifications

• Bachelor’s degree or PhD in computer science or technology with direct experience working with AI Models
• Strong proficiency in Python, C++, Java programming and RESTful APIs
• Familiarity with service-oriented architecture (SOA) and cloud-based integration patterns
• Development Experience using models like; LangGraph, LangChain, Autogen, CrewAI, n8n, Vertex AI
• Exposure to MLflow, Kubeflow, or similar MLOps platforms
• Experience with TensorFlow, PyTorch, or Keras for building neural networks
• Proficiency with development tools (VS Code, Jupyter, Git)

Technical Learning Opportunities

• Full MLOps Lifecycle: Gain end-to-end experience from model development to production deployment and monitoring
• Advanced AI Techniques: Work with cutting-edge approaches including reinforcement learning, causal inference, and knowledge graphs
• Production-Grade Systems: Learn to build scalable, resilient AI systems that handle real-world problems
• Cloud-Native Development: Master cloud infrastructure and services for ML workloads
• Real-Time Processing: Implement streaming data pipelines and real-time inference systems
• Industry-Specific AI: Apply ML techniques to solve complex business problems
• Technical Mentorship: Work directly with senior AI engineers and data scientists

Working Conditions

Location Requirements
Remote

Physical Requirements
This is a largely sedentary role.

Direct Reports
None

Quantisage is an equal-opportunity employer. To ensure equal employment and advancement opportunities for all individuals, we base all employment decisions on merit, qualifications, abilities, and an individual’s conduct and performance. We will not make any decisions or discriminate against any employee or applicant based on race, color, religion, creed, national origin or ancestry, ethnicity, sex (including pregnancy), gender (including sexual orientation, gender identity, and status as a transgender or transsexual individual), age, physical or mental disability, citizenship, past, current, or prospective service in the uniformed services, genetic information, or any other characteristic protected against discrimination under the law. Quantisage complies with applicable federal, state, and local laws governing nondiscrimination in employment.

Preferred Skills

• Deep Learning: Experience with TensorFlow, PyTorch, or Keras for building neural networks
• Big Data Tools: Familiarity with Spark, Hadoop, or similar distributed computing frameworks
• Cloud Platforms: Hands-on experience with AWS, Azure, or GCP (especially compute, storage, and ML services)
• Containerization: Experience with Docker and container orchestration (Kubernetes preferred)
• Streaming Data: Knowledge of Kafka, Kinesis, or similar streaming technologies
• MLOps Tools: Exposure to MLflow, Kubeflow, or similar MLOps platforms
• Graph Databases: Familiarity with Neo4j, Amazon Neptune, or graph query languages (Cypher, Gremlin)
• NLP Experience: Understanding of NLP techniques and libraries (spaCy, NLTK, Hugging Face)
• API Development: Experience building RESTful APIs using FastAPI, Flask, or similar frameworks