Open to opportunities

Rafael Paladini

@rafaelpaladini

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M.Sc. candidate and software engineer specializing in algorithms, ML, and large language model training.

Brazil

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What I'm looking for

I seek roles where I can apply algorithms, ML, and LLM training in collaborative teams, contribute to production systems, and continue research-driven impact.

I am an M.Sc. candidate in Systems and Computer Engineering with over three years of hands-on experience in software development, data science, operations research, and LLM training. I have led small technical teams, designed programming benchmarks for state-of-the-art language models, and contributed to RLHF pipelines for coding assistants and simulators.

My background spans full-stack engineering, metaheuristic solver development, and applied research in maritime logistics with a Q1 journal publication and conference awards. I communicate fluently in Portuguese and English, mentor students, and deliver production-ready systems integrating ML workflows and data warehouses.

Experience

Work history, roles, and key accomplishments

LLM Trainer / Pod Lead

Turing

Sep 2024 - Nov 2025 (1 year 2 months)

Led pods of 4–6 members to coordinate tasks, review deliverables, and ensure QA; designed programming challenges to benchmark LLMs and contributed to RLHF pipelines for coding assistants and simulators.

Prompt Engineering RLHF Pipeline Python LLM Evaluation Quality Assurance POD Leadership Data Annotation

Operational Research Intern

FROG (PUC-Rio)

Feb 2024 - Dec 2024 (10 months)

Researched and implemented metaheuristics for maritime inventory routing problems and co-authored a paper published in Computers & Operations Research; presented findings at SBPO, winning 2nd place for undergraduate research.

Meta Heuristics Iterated Local Search Maritime Logistics Research Scientific Writing Optimization

Operational Research Intern

Accenture

Feb 2024 - Sep 2024 (7 months)

Developed and refined an ILS-based ship routing solver in C#, applying metaheuristics and data structures to improve solver performance for maritime routing problems.

C Meta Heuristics Iterated Local Search Algorithm Design Data Structures Optimization Performance Tuning Operational Research

Junior Developer

Gávea Investimentos

Feb 2023 - Feb 2024 (1 year)

Engineered and deployed full-stack applications and automated data pipelines for economics and ML teams using .NET, Akka, and Python; implemented a data warehouse to streamline ML workflows.

.NET Akka Python Data Pipelines Data Warehousing Full Stack ETL Machine Learning Integration

Undergraduate Teaching Assistant

PUC-Rio

Feb 2022 - Jul 2023 (1 year 5 months)

Assisted Python programming and algorithms courses by conducting review sessions, grading assignments and exams, and mentoring over 50 students to improve course outcomes.

Python Algorithms Teaching Mentoring Grading Student Support Course Assistance

Data Science Intern

Jobzi

Jul 2022 - Feb 2023 (7 months)

Contributed to a UNICEF-commissioned project analyzing the impact of school connectivity on child employability, focusing on data analysis and predictive modeling.

Data Analysis predictive modeling Python Statistics Data Visualization Research

Education

Degrees, certifications, and relevant coursework

Universidade Federal do Rio de Janeiro

Master of Science, Systems and Computer Engineering

2025 -

Activities and societies: Recipient of M.Sc. scholarship; research in algorithms and combinatorics.

M.Sc. candidate in Systems and Computer Engineering with focus on Algorithms and Combinatorics, enrolled January 2025 and currently pursuing graduate research.

Pontifícia Universidade Católica do Rio de Janeiro

Bachelor of Science, Computer Science

2021 - 2024

Activities and societies: Undergraduate teaching assistant (Python and Algorithms); research with FROG on maritime inventory routing; multiple hackathon and competition awards.

Bachelor of Computer Science completed March 2021 to December 2024 with coursework and research experience in algorithms, data structures, and machine learning.