PH - Intern, Machine Learning & GenAI Engineering Track at Thinking Machines Data Science, Inc.

Taguig, Metro Manila, Philippines -

Full Time

Start Date

Immediate

Expiry Date

25 Jun, 26

Salary

0.0

Posted On

27 Mar, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Pandas, Numpy, Matplotlib, Jupyter, Git, Apis, Data Structures, Llm, Genai, Statistical Experiments, Algorithmic Coding, Kaggle, Technical Writing, Communication

Industry

IT Services and IT Consulting

Description

Working at Thinking Machines Thinking Machines is a technology consultancy building AI & data platforms to solve high-impact problems for our clients. Our vision is for the Philippines to become a global hub for data science. To do that, we create data cultures, one organization at a time. We’re a company composed of intellectually curious, civic-minded, forever-learning individuals. We believe great data science products are built with care for people and the best way to drive inclusive innovation is to start with a diverse team. Our field of work is incredibly dynamic, so we want to work with people who are committed to growing with us. We want to hire people who can demonstrate an ability to learn, then provide them with personalized coaching, growth opportunities, and a great working environment to get them to world-class. Role Description This intern position is a great opportunity for Filipino college students looking for an immersive internship or fresh graduates and career shifters just starting in the data science industry. Build your skills in researching, testing, and scaling machine learning models to support GenAI and LLM developments. This year, we're looking for interns who are ready to learn, get hands-on experience, receive mentorship from a member of our team, and work in a hybrid-remote setup. We're also offering a fully remote internship option for candidates based outside of Metro Manila or Greater Metro Manila. Chosen interns will have an opportunity to run experiments, design and evaluate machine learning and GenAI models with our Machine Learning & GenAI Engineering Team. We're looking for individuals who: Are university students (3rd year and above) or fresh graduates (batch 2026) from courses such as Management/Management Engineering, Mathematics, Decision Science, Computer Science, Computer Engineering, Data Science or similar fields Are career shifters from other fields and new to data science and tech consultancy Can commit to a full-time (40 hours per week), fully-paid, and hybrid-remote internship for 10 weeks Can show a track record of being able to work hard, solve problems, learn independently, do quality work, and communicate effectively Can strongly demonstrate skill depth in some areas (e.g. running statistical experiments, building GenAI or automation tools, creating visualizations, great at algorithmic coding competitions, respectable rank on Kaggle, etc.) Have a personal machine or laptop and a stable internet connection Qualifications This intern track is for you if you have any (but not necessarily all) of the following skills: Python (Pandas, Numpy, Matplotlib, Jupyter) Git APIs (REST, SDK usage) Working knowledge of data structures (JSON, CSV) Fundamentals of LLMs (e.g., prompting, tokens, context) Working knowledge of GenAI and AI systems Research and technical writing Effective written and verbal communication Bonus Points if you have experience in the following: Building or shipping a GenAI project Cloud technologies (e.g. GCP, AWS) Conducting user interviews Logistics 10 weeks starting June 8, 2026 Paid internship Full-time, hybrid-remote work Send in your resume and fill out the form below to kickstart your application! Deadline of Application is on April 5, 2026, 11:59 PM GMT+8.

Responsibilities

Interns will build skills in researching, testing, and scaling machine learning models to support GenAI and LLM developments. Chosen interns will run experiments, design, and evaluate machine learning and GenAI models with the Machine Learning & GenAI Engineering Team.