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AI Engineer

Full-Time AI Engineers from $2,000/month

Get started with vetted AI Engineers in as little as 10 days and save up to 80%. Kuubiik manages contracts, payments, and HR core processes, helping you avoid compliance gaps and unnecessary risk.

Trusted by 500+
fast-growing companies

Trusted by 500+ fast-growing companies

How much does it cost to outsource a AI Engineer?

Compare monthly outsourcing costs and skill levels across junior, mid-level, and senior AI Engineers.

Junior AI Engineer

1 - 2 years of experience

  • Degree in Computer Science, Mathematics, or a related field
  • 1-2 years of hands-on experience with machine learning projects
  • Proficiency in Python and core ML libraries (scikit-learn, TensorFlow, or PyTorch)
  • Solid understanding of supervised and unsupervised learning techniques
  • Experience working with structured datasets and basic feature engineering
  • Strong willingness to learn and apply new AI frameworks

Southeast Asia

$2,000 - $3,000 /mo

LATAM

$4,000 - $5,500 /mo

USA

$8,000 - $10,000 /mo

Mid-Level AI Engineer

3 - 5 years of experience

  • Degree in Computer Science, AI, or related field
  • 3+ years of experience building and deploying ML models
  • Proficient in deep learning frameworks (TensorFlow, PyTorch, Keras)
  • Experience with model training pipelines, hyperparameter tuning, and evaluation
  • Solid understanding of NLP, computer vision, or time-series modeling
  • Ability to translate business problems into AI solutions

Southeast Asia

$3,000 - $4,500 /mo

LATAM

$5,500 - $7,500 /mo

USA

$12,000 - $15,000 /mo

Senior AI Engineer

6+ years of experience

  • Advanced degree or extensive portfolio in AI and ML preferred
  • 6+ years of experience designing and shipping production-grade ML systems
  • Deep expertise in model architecture, optimization, and scalability
  • Proven experience leading AI projects end-to-end from research to deployment
  • Strong knowledge of MLOps practices, CI/CD for models, and cloud AI platforms
  • Ability to mentor teams and drive AI strategy across the organisation

Southeast Asia

$4,500 - $6,500 /mo

LATAM

$7,500 - $11,000 /mo

USA

$15,000 - $20,000 /mo

Kuubiik World Map

AI Engineer responsibilities and core areas of work

Model Development

  • An AI Engineer designs and builds machine learning models using frameworks like TensorFlow, PyTorch, and scikit-learn.
  • Select appropriate algorithms and architectures based on the problem type and available data.
  • Perform iterative model training, evaluation, and fine-tuning to hit performance benchmarks.

Data Preparation

  • Source, clean, and transform raw datasets into training-ready formats.
  • Conduct exploratory data analysis (EDA) to uncover patterns, outliers, and feature opportunities.
  • Build reproducible data pipelines that support consistent model training and evaluation.

Model Deployment

  • Package and deploy ML models to production environments via REST APIs or cloud-native services.
  • Integrate models into existing applications and backend systems with minimal friction.
  • Monitor deployed models for performance degradation, data drift, and accuracy over time.

Experimentation & Research

  • Run structured experiments to test hypotheses, compare approaches, and document findings.
  • Stay current with advances in AI research and evaluate new techniques for practical application.
  • Prototype proof-of-concept solutions to validate feasibility before full development.

Feature Engineering

  • Identify and create meaningful features from raw data that improve model accuracy.
  • Apply dimensionality reduction, encoding, and normalisation techniques as needed.
  • Collaborate with data engineers to ensure feature pipelines are scalable and maintainable.

Cross-functional Collaboration

  • An AI Engineer works closely with data engineers, product managers, and software developers to align on AI requirements.
  • Translate complex model outputs into clear, actionable insights for non-technical stakeholders.
  • Participate in code reviews and contribute to team knowledge sharing on AI best practices.

Tools & Infrastructure

  • Leverage cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML) for scalable training and inference.
  • Use experiment tracking tools like MLflow, Weights & Biases, or Neptune to manage model versioning.
  • Contribute to building and maintaining the shared ML tooling and infrastructure used by the team.

Finding the right resource has never been more flexible

Related to

Roles

ASIA: From $2,000 - $2,800/month

LATAM: From $3,800 - $5,500/month

AVG. US SALARY: $12,000 - $15,500/month

SAVINGS: 50 - 80%

ASIA: From $1,500 - $2,200/month

LATAM: From $2,800 - $4,200/month

AVG. US SALARY: $8,500 - $11,000/month

SAVINGS: 50 - 80%

ASIA: From $1,500 - $2,200/month

LATAM: From $2,800 - $4,000/month

AVG. US SALARY: $8,000 - $10,500/month

SAVINGS: 50 - 80%

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