AI/ML Engineering Intern (Immediate Start!)

Please note that this role requires an immediate start date for the selected candidates.

Location: Remote / Hybrid
Type: Internship (3–6 months) 
Start Date:  Immediate Start
Compensation: Stipend / Internship Credit
Conversion: High-performing technical interns may be offered a full-time role upon completion

About Alpheva AI

Alpheva AI is building the world’s first agentic financial advisor — an intelligent platform that helps users plan, invest, and grow their wealth through AI-driven insights and autonomous financial actions.

Our mission is to make premium financial advice accessible, intelligent, and 10x cheaper than traditional models. Founded by a team of experienced entrepreneurs and engineers, Alpheva is at the intersection of AI, fintech, and behavioral finance, redefining how people manage money in the age of automation.

Role Overview

We’re seeking an AI/ML Engineering Intern to join our fast-growing team. In this role, you’ll work directly with the founding team to design, build, and deploy machine learning solutions that power our AI-driven financial platform.

This is a high-impact internship for someone who wants to learn how AI, data, and engineering come together in a startup — and potentially transition into a full-time role post-internship.

Key Responsibilities

Develop and prototype AI/ML models to support product features such as personalized financial insights, risk assessment, and recommendation systems.

Clean, process, and analyze large structured and unstructured datasets to extract useful patterns and train models.

Evaluate, fine-tune, and optimize models for performance, scalability, and interpretability.

Work with APIs, data pipelines, and cloud infrastructure (AWS, GCP, or Azure) to deploy models into production.

Collaborate with product and design teams to translate business problems into machine learning solutions.

Conduct research on new ML techniques, LLMs, and generative AI tools relevant to financial intelligence applications.

Document experiments, results, and technical processes to ensure reproducibility and knowledge sharing.

What We’re Looking For

Pursuing a Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.

Solid understanding of Python and ML libraries such as pandas, scikit-learn, TensorFlow, or PyTorch.

Familiarity with data preprocessing, feature engineering, and model evaluation techniques.

Experience or interest in LLMs, NLP, or generative AI is a strong plus.

Knowledge of SQL, REST APIs, or data pipeline tools preferred.

Strong analytical and problem-solving mindset, with attention to detail.

Curious, self-driven, and comfortable working in a fast-paced, early-stage startup environment.

What You’ll Gain

Hands-on experience building and deploying AI models in a real-world fintech product.

Exposure to modern MLOps workflows, data engineering, and applied generative AI.

Mentorship from experienced founders and AI practitioners.

A chance to make a visible impact and earn a full-time offer based on performance.