Junior Machine Learning Engineer

Docket

Junior Machine Learning Engineer at Docket developing Intelligent Document Processing solutions and collaborating with technical and product teams.

Posted 7/22/2026full-timeRemote • BrasilJuniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Intelligent Document Processing, leveraging Python and SQL for data manipulation and analysis, while applying statistical techniques to derive insights from structured datasets. Proficient in Generative AI, LLMs, and orchestration logic to enhance document workflows and product development.

Highest-signal resume keywords

Python ProgrammingSQL Data AnalysisGenerative AI FundamentalsPrompt EngineeringNatural Language Processing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ManipulationStatistical TechniquesAPI ConsumptionMultivariate AnalysisHypothesis TestingDocument ClassificationComplex QueriesData ModelingMachine Learning FrameworksGraph-Based Flows

Soft Skills

Excellent CommunicationCuriosityResilienceProactivityCollaboration

Tools & Technologies

ChatGPTClaudeCursorGitHub CopilotPandasNumPyScikit-learnTensorFlowPyTorchN8n

Industry Keywords

Intelligent Document ProcessingData ScienceMachine LearningAI ToolsRetrieval-Augmented GenerationDocument ExtractionWorkflow OrchestrationTechnical LeadershipData EngineeringProduct Management

Tech Stack

Tools & technologies

NumpyPandasPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Support the development of IDP (Intelligent Document Processing) solutions: Contribute to creating, training, tuning models and fine-tuning for extracting unstructured data from complex documents.
Build the future of agentic AI: Assist in orchestrating workflows using frameworks such as LangGraph, n8n, and others, connecting document extraction to approval and formalization pipelines.
Transform data into products: Apply statistical techniques and data analysis to the structured datasets produced by our IDPs, helping identify patterns and insights that will become new AI products for our clients.
Collaborate with technical, product and commercial teams: Work side by side with Technical Leadership, Data Engineering, Product Managers and the Front-end team, evaluating, supporting and improving the transition of proofs of concept (PoCs) to production solutions.
Ensure quality and monitoring: Help evaluate model outputs (LLMs, RAGs and classical models), test prompts and document processes, ensuring solutions are accurate and scalable.
Learn and innovate: Stay up to date with the state of the art in Generative AI, bringing curiosity, ideas and proactivity to solve bottlenecks in our document pipeline.

Requirements

What you’ll need

Completed degree or near completion in Computer Science, Engineering, Statistics, Mathematics, Physics, Data Science or related STEM fields.
Clear understanding of statistics and programming logic (know why to use a technique, not just how to import a library).
Proficiency in Python focused on data manipulation and API consumption.
Practical knowledge of SQL for extracting, joining and analyzing data in relational databases.
Hunger to learn, resilience to handle errors during experiments and excellent communication to ask for help, clarify doubts and present ideas clearly.
Fluency with AI tools: Daily use of tools such as ChatGPT, Claude, Cursor or GitHub Copilot to accelerate your development and study flow.
Programming and analysis: Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) and SQL (complex queries and data modeling).
Generative AI and LLMs: Solid fundamentals in Prompt Engineering and a theoretical/practical understanding of how LLMs (OpenAI, Anthropic) and RAG (Retrieval-Augmented Generation) architectures work.
Natural Language Processing (NLP) and Computer Vision: Basic understanding of concepts behind text extraction and document classification.
Applied statistics: Ability to analyze large volumes of structured data and apply multivariate analyses or hypothesis testing to extract business value.
Orchestration logic: Understanding of how APIs communicate and the logic of graph- or node-based flows (preparing to work with Agents).

Benefits

Comp & perks

Meal and food allowance via Flash for when hunger strikes.
Health and dental insurance to take care of you.
Life insurance for added peace of mind.
Petlove benefits, because at Docket we understand your furry family matters too.
Conexa Saúde, psychological support at your fingertips.
Wellhub and TotalPass to keep your body moving.
Galena, because learning and development are essential.
Partnership with Sesc, access to leisure and cultural activities.
Childcare assistance for parents with children up to 5 years old.
Baby Cash when the family grows.
Birthday month day off to celebrate as you deserve.
Working hours: 44 hours per week