IT & Technology Job Vacancy at Virtual Nation—Machine Learning Engineer

Build Intelligent Systems. Develop Machine Learning Solutions. Work Remotely.

Virtual Nation is seeking a skilled and innovative Machine Learning Engineer to design, develop, deploy, and maintain machine learning models and intelligent systems that support business and technology objectives. This opportunity is ideal for candidates with experience in machine learning, artificial intelligence, Python, data science, software engineering, deep learning, statistical modelling, or related fields.

If you are interested in this job opening you can continue on this page for more information on the job description and for the official online recruitment channel to begin application.

Applications are invited for the position below:

Job Title: Machine Learning Engineer

Location: Remote

Description

We are looking for a Machine Learning Engineer to improve and train the AI systems already powering our products. You’ll take our existing builds from good to exceptional, refining and retraining models that solve real business problems at scale.
You will improve, retrain, and fine-tune our existing machine learning models and AI systems. This includes data preprocessing, model optimisation, and continuous monitoring once models are live. Your focus is on strengthening what we’ve already built, not starting from scratch.

Key Responsibilities

Improve and retrain existing machine learning models to boost accuracy and reliability
Perform data exploration, cleaning, and preprocessing to support model improvements
Fine-tune and optimise existing models for better performance and scalability
Monitor deployed models and make ongoing adjustments as needed
Build and improve APIs for AI services already integrated into our products
Work with Large Language Models (LLMs) and related frameworks where relevant
Stay current with new developments in machine learning and AI, applying useful techniques to existing systems
Collaborate with product managers, developers, and other stakeholders to understand and meet AI requirements
Document methodologies and workflows for reproducibility and knowledge sharing

Performance Metrics & KPIs

Accuracy and performance improvements on existing models
Model uptime and reliability in production
Turnaround time on model improvements and fixes
Measurable gains from retraining efforts
Quality and clarity of documentation

Skills & Competencies Required
Must-have:

7+ years of overall experience in a technical role
5+ years of hands-on experience in machine learning and AI, with a proven track record of improving models in production
Strong programming skills in Python
Strong knowledge of ML frameworks and libraries (TensorFlow, PyTorch, Scikit-learn)
Experience with data manipulation tools (Pandas, NumPy, SQL)
Experience with cloud platforms (AWS, GCP, or Azure)
Strong understanding of statistics, probability, and applicable mathematical concepts
Excellent communication and collaboration skills
Ability to work independently with minimal supervision

Nice-to-have:

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, Engineering, or a related field
Experience with LLMs, Hugging Face, LangChain, or similar frameworks
Knowledge of FastAPI or Flask for AI deployment
Experience with vector databases (Pinecone, FAISS, ChromaDB, Weaviate)
Familiarity with Docker and Git
Strong portfolio or GitHub showcasing AI/ML projects

What Success Looks Like

At 90 days: You’ve reviewed our existing AI systems, identified key improvement areas, and begun implementing measurable performance gains.
At 1 year: Our AI systems are noticeably more accurate, scalable, and reliable. You’ve led at least one major improvement to an existing model or AI feature

Compensation & Benefits