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FocusKPI, Inc.

[Internal] Machine Learning/AI Engineer Trainee

FocusKPI, Inc., San Francisco, California, United States, 94199


Job Title:

Machine Learning/ AI Engineer Trainee Location:

Remote in United States (EST Preferred) Type:

Full-Time / Unpaid Trainee Program Company:

FocusKPI Please submit your resume and a brief cover letter outlining your experience with relevant projects, coursework/work experience, and why you’re interested in this role to

danz@focuskpi.com

.

We are excited to invite aspiring software engineers and AI enthusiasts to join our 3-month AI Trainee Program, designed to fast-track your skills in building and implementing AI solutions. This program provides hands-on experience with real-world projects, enabling you to enhance both your software engineering and AI expertise. Under the mentorship of our experienced team, you’ll refine your skills in designing scalable systems, deploying machine learning (ML) models, and building APIs.

Exceptional performance during the program may lead to a paid internship opportunity, setting the stage for a promising career in AI and software development. About the Program:

This program is ideal for individuals passionate about

AI and software engineering , particularly in Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), and software deployment. You’ll gain practical experience in building and deploying machine learning models, integrating them into vector-based solutions, and creating robust software infrastructure for scalable applications. The program focuses on your growth, providing you with the tools and knowledge to succeed in the dynamic field of AI-driven software development. Ideal Qualifications:

We welcome candidates with the following background: Bachelor’s or Master’s degree in

Computer Science ,

Data Science , or related fields.

Interest and hands-on experience with

NLP ,

RAG , and

machine learning frameworks .

Proficiency in

Python

and API development using frameworks like

FastAPI .

Strong problem-solving skills and a detail-oriented approach to software development.

Key Learning Opportunities:

Gain hands-on experience in

designing and implementing NLP models

for tasks such as text classification, sentiment analysis, and named entity recognition.

Learn and apply

Retrieval-Augmented Generation (RAG)

frameworks integrated with vector-based solutions to enhance system performance.

Build and maintain

scalable APIs

(e.g., using FastAPI) for real-world deployment of AI models.

Develop expertise in

containerization tools

like Docker to streamline deployment and scalability.

Gain practical experience in implementing

CI/CD pipelines

for automated testing, integration, and deployment to ensure reliable and efficient delivery of AI solutions.

Acquire practical knowledge in

data preprocessing , feature extraction, and building robust data pipelines for large-scale applications.

Work on integrating ML models into

end-to-end production systems , focusing on scalability and performance.

Strengthen your

software engineering skills , with exposure to tools like Python, FastAPI, and cloud platforms (AWS, Google Cloud, Azure).

Enhance your

collaboration and documentation skills

by working in a dynamic, remote team environment.

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