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AWS SageMaker
Mercor
Scale AINo subject matter listed
Image
Text
Computer Code Programming
Bounding Box
RLHF
Fine-tuning
Evaluation/Rating
Computer Programming/Coding
Prompt + Response Writing (SFT)
Segmentation
Text SummarizationMy strongest AI training experience has been through Alignerr/Anthropic and Fleet Fellowship. Through Alignerr/Anthropic, I worked on Claude evaluation across coding, mathematical reasoning, structured data, and general reasoning tasks. This involved reviewing model outputs against detailed rubrics, checking instruction following, identifying hallucinations, comparing responses through A/B evaluations, and assessing whether outputs matched deterministic expected results. I also worked with Python validation checks and Git-based workflows, including commit hashes, repository states, and evaluation artefacts, which made the evaluation process more reproducible and technically reliable. Through Fleet Fellowship, I designed complex prompts and realistic multi-step workflows used to evaluate generative AI systems across finance, HR, and operational environments. This work focused on testing whether models could follow detailed instructions, reason through business processes, handle edge cases, and produce outputs that matched clear success criteria. Alongside this, I have worked on Cypher Evals for STEM and coding response ranking, Aether for image review and source-image identification, and recent OpenSees/CAD engineering simulation tasks. My Mechanical Engineering background, Python/C++ experience, and technical AI evaluation work allow me to handle both generalist AI training tasks and more domain-specific projects.
TextPrompt + Response Writing (SFT)Designed complex prompts and realistic multi-step workflows used to evaluate generative AI systems across finance, HR, and operational environments. The work focused on testing whether AI systems could follow detailed instructions, reason through business processes, handle edge cases, and produce outputs that matched clear success criteria.
DocumentEvaluation/RatingWorked on STEM and coding AI training projects where I evaluated and ranked pairs of AI-generated responses across multiple axes, including correctness, reasoning quality, instruction following, clarity, and overall helpfulness. This involved applying project rubrics, identifying technical errors, comparing response quality, and giving structured feedback to improve model performance.
Computer Code ProgrammingRLHFWorked on AI training and evaluation projects involving Claude model outputs across coding, mathematical reasoning, structured data, and general reasoning tasks. The work involved reviewing model responses, checking instruction following, identifying hallucinations, comparing response quality, and applying detailed rubrics to assess model performance.
Image
Data CollectionWorked on the Aether project, reviewing image-based tasks and identifying source images according to project guidelines. The work involved assessing visual information, checking image relevance, following annotation rules, and supporting the preparation of accurate training data for AI systems.
MSc, Renewable Energy with AI and Data science: Geology and Geophysics
BEng, Mechanical Engineering
