Software Engineer (AI Training)

ERecruiter

Job Location:

Lagos - Nigeria

Salary: Not Disclosed

Experience Required: 3years

Posted on: 3 hours ago

Vacancies: 1 Vacancy

Job Summary

Our client is seeking a skilled Software Engineer with a focus on AI Training to support their team. The ideal candidate will contribute to the development and refinement of machine learning models by building robust data pipelines designing annotation workflows and collaborating with AI research teams to improve model performance at scale.

Job Responsibilities

Design build and maintain data pipelines that support AI model training and evaluation workflows.
Develop tooling and automation to streamline data collection labeling and preprocessing processes.
Collaborate with ML researchers and data scientists to understand model requirements and translate them into engineering solutions.
Implement quality control mechanisms to ensure training data accuracy consistency and integrity.
Build and maintain internal platforms and APIs that support annotation and human feedback workflows (RLHF).
Monitor and optimize pipeline performance scalability and reliability in production environments.
Contribute to documentation code reviews and engineering best practices across the team.

Job Requirements

35 years of software engineering experience with exposure to AI ML or data engineering environments.
Proficiency in Python and at least one additional language (Go Java or TypeScript).
Experience building and maintaining data pipelines using tools such as Apache Airflow Spark or equivalent.
Familiarity with machine learning concepts model training workflows and evaluation methodologies.
Experience working with large datasets data annotation platforms or labeling tools.
Strong understanding of REST APIs microservices and cloud infrastructure (AWS GCP or Azure).
Excellent problem-solving skills and ability to work independently in a remote environment.

Preferred Qualifications

Experience with Reinforcement Learning from Human Feedback (RLHF) or similar human-in-the-loop training methodologies.
Familiarity with LLM training infrastructure and model evaluation frameworks.
Experience with vector databases embedding or retrieval-augmented generation (RAG) pipelines.
Prior experience at an AI-focused company or research lab.

Job Responsibilities

Design build and maintain data pipelines that support AI model training and evaluation workflows.
Develop tooling and automation to streamline data collection labeling and preprocessing processes.
Collaborate with ML researchers and data scientists to understand model requirements and translate them into engineering solutions.
Implement quality control mechanisms to ensure training data accuracy consistency and integrity.
Build and maintain internal platforms and APIs that support annotation and human feedback workflows (RLHF).
Monitor and optimize pipeline performance scalability and reliability in production environments.
Contribute to documentation code reviews and engineering best practices across the team.

Job Requirements

35 years of software engineering experience with exposure to AI ML or data engineering environments.
Proficiency in Python and at least one additional language (Go Java or TypeScript).
Experience building and maintaining data pipelines using tools such as Apache Airflow Spark or equivalent.
Familiarity with machine learning concepts model training workflows and evaluation methodologies.
Experience working with large datasets data annotation platforms or labeling tools.
Strong understanding of REST APIs microservices and cloud infrastructure (AWS GCP or Azure).
Excellent problem-solving skills and ability to work independently in a remote environment.

Preferred Qualifications

Experience with Reinforcement Learning from Human Feedback (RLHF) or similar human-in-the-loop training methodologies.
Familiarity with LLM training infrastructure and model evaluation frameworks.
Experience with vector databases embedding or retrieval-augmented generation (RAG) pipelines.
Prior experience at an AI-focused company or research lab.