Demonstrates foundational Python skills and a basic understanding of machine learning concepts, with the ability to work with structured data and integrate APIs. Strong attention to detail and clear communication skills are essential for documenting processes and collaborating with cross-functional teams.

Highest-signal resume keywords

Python ProgrammingMachine Learning ConceptsREST APIsGit Version ControlData Validation

Tech Stack

Tools & technologies

CloudDockerFlaskJavaNumpyPandasPythonPyTorchScikit-LearnSpringSpring BootSpringBootSQLTensorflow

About the role

Key responsibilities & impact

Build clearly scoped Python components, scripts and integrations for AI-enabled features
Prepare and validate datasets, checking formats, missing values and labelling quality
Integrate model and LLM APIs into Evolve workflows
Support prompt configuration, structured outputs and response validation
Create and run repeatable evaluations covering typical, edge and failure scenarios
Compare outputs against agreed criteria and document errors, limitations and regressions
Investigate unreliable outputs and integration failures, recording findings and escalating concerns
Apply approved privacy and security practices for personal data, credentials and confidential information
Support deployment and monitoring under guidance, including API failures, response time, usage and cost
Implement fallback or human-review steps
Use Git, tests and code reviews to maintain readable code
Document APIs and evaluation results, apply feedback, and communicate progress and blockers
Work with Software Engineers, QA Engineers and Product across Evolve teams

Requirements

What you’ll need

Entry-level role; internship, academic or personal project experience suitable
Degree in Computer Science, Software Engineering, Data Science or a related field, or equivalent practical training supported by relevant projects
Foundational Python skills shown through coursework, an internship or a working project
Basic understanding of machine learning concepts, evaluation metrics and limits of model outputs
Familiarity with REST APIs, HTTP and JSON, Git, automated tests and debugging in an existing codebase
Ability to work with structured data, use documentation and explain the approach and results of a technical task
Attention to detail and sound judgement about handling data
Clear communication and willingness to seek and apply feedback
Nice to have: exposure to FastAPI or Flask, pandas or NumPy
Nice to have: project using a model API, LLM, scikit-learn, PyTorch or TensorFlow
Nice to have: familiarity with SQL, Docker, Java/Spring Boot, cloud concepts or CI workflows

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonMachine LearningData ValidationAPI IntegrationAutomated TestingDebuggingStructured Data HandlingEvaluation MetricsFastAPIFlask

Soft Skills

Attention to DetailClear CommunicationWillingness to Seek Feedback

Tools & Technologies

GitSQLDockerNumPyPandasScikit-learnPyTorchTensorFlowJava/Spring BootCI Workflows

Industry Keywords

AI-Enabled FeaturesData ScienceSoftware EngineeringPrivacy PracticesSecurity Practices