AI & Automation · AI & Data Engineers

AI & data engineers who ship models to production.

Hire ML engineers, data engineers, MLOps specialists, and AI architects from a company that has shipped 8+ AI-led products. Engineers who embed in your team and deliver production-grade AI from week one.

ML engineering & model development

Data engineering & ETL pipelines

MLOps & model monitoring

AI architecture & strategy

Computer vision & NLP

LLM fine-tuning & RAG systems

AI products shipped

Production AI systems — not proofs-of-concept gathering dust.

400+

Engineers on bench

ML, data, and MLOps engineers ready to start within 1–2 weeks.

98%

Model accuracy floor

Production models validated on real-world data, not toy datasets.

48hr

Talent shortlist

Vetted AI engineer profiles proposed within two business days.

Why MetaDesign

AI engineers who ship, not just experiment.

8+ AI products in production. ML, data, MLOps, and GenAI engineers embedded in your team.

Production AI, Not Science Projects

Our engineers have shipped 8+ AI products to production. They build models with monitoring, retraining, and drift detection — not just Jupyter notebooks that never leave the lab.

Full-Stack Data Engineering

From ingestion to insight — our data engineers build the pipelines, warehouses, and feature stores that feed your ML models. No gaps between data and intelligence.

Your Team, Your Workflow

We embed into your existing stack — Databricks, Snowflake, SageMaker, Vertex AI. Your tools, your ceremonies, your standards. Indistinguishable from in-house hires.

Teams shipping with MetaDesign

Selected work

Case studies.

View all

JobDroid

Embedded an AI squad that built an end-to-end recruitment automation platform using LlamaIndex, LangChain, and OpenAI — automating resume parsing, candidate matching, and shortlisting for Australia's leading job platform.

JobDroid

60%

faster shortlisting

Automated

resume parsing

Fraud Detection Engine

Deployed an ensemble ML model for real-time fraud detection processing millions of transactions — 98% accuracy with 40% fewer false positives and sub-second inference latency.

Fraud Detection Engine

Deployed an ensemble ML model for real-time fraud detection processing millions of transactions — 98% accuracy with 40% fewer false positives and sub-second inference latency.

98%

detection rate

40%

fewer false positives

SCOPE.

MATCH.

EMBED.

SHIP.

ML Engineering

PyTorch, TensorFlow, scikit-learn — custom models for classification, regression, recommendation, and anomaly detection trained on your domain data.

Data Engineering

Snowflake, BigQuery, Databricks, dbt — scalable data pipelines, warehouses, and lakehouses that make your data ML-ready.

MLOps & Deployment

MLflow, SageMaker, Vertex AI — model versioning, A/B serving, drift detection, and automated retraining pipelines for production ML.

LLM & GenAI

Fine-tuning, RAG pipelines, prompt engineering, and AI agent development on OpenAI, Gemini, Claude, and open-source models.

Computer Vision

Object detection, image classification, video analytics, and OCR — production vision systems for manufacturing, healthcare, and security.

Analytics & BI

Tableau, Power BI, Looker — executive dashboards, predictive analytics, and self-service analytics platforms built on solid data foundations.

Our Approach

AI & Data Engineers: Our Proven Process

Scope

Define your AI/data requirements, team structure, and engineering culture expectations.

Match

We shortlist vetted AI & data engineers within 48 hours — live coding assessments, ML system design, and domain fit.

Embed

Engineers join your daily standups, use your tools, and follow your development practices from day one.

Ship

Production models with monitoring, versioning, and automated retraining — not just prototypes.

Scale

Add or rotate engineers as your AI roadmap evolves. No long-term lock-in.

Scope

Define your AI/data requirements, team structure, and engineering culture expectations.

Match

We shortlist vetted AI & data engineers within 48 hours — live coding assessments, ML system design, and domain fit.

Embed

Engineers join your daily standups, use your tools, and follow your development practices from day one.

Ship

Production models with monitoring, versioning, and automated retraining — not just prototypes.

Scale

Add or rotate engineers as your AI roadmap evolves. No long-term lock-in.

Customer Value

Why enterprises trust us
with their AI.

Real outcomes our clients report within the first engagement cycle.

Higher automation rates

Eliminate repetitive tasks and free your team to focus on strategic work.

Measurable accuracy

AI models with tracked precision, recall, and F1 scores — not guesswork.

Faster decision-making

Real-time insights and predictions that accelerate business decisions.

Reduced operational cost

Automation that pays for itself within the first quarter.

Production-grade reliability

Guardrails, monitoring, and fallback logic built into every AI system.

Knowledge transfer

Your team learns to maintain and extend AI systems independently.

Stack

Tools our AI & Data Engineers
Developers
ship with.

Foundation models, deep learning frameworks, vector retrieval, and workflow orchestration pre-wired into production pipelines. We build scalable AI architectures you can own completely.

PyTorch

TensorFlow

scikit-learn

XGBoost

Hugging Face

Snowflake

BigQuery

Databricks

dbt

Airflow

PyTorch

TensorFlow

scikit-learn

XGBoost

Hugging Face

Snowflake

BigQuery

Databricks

dbt

Airflow

MLflow

SageMaker

Vertex AI

Weights & Biases

LangChain

LlamaIndex

OpenAI

Pinecone

Weaviate

MLflow

SageMaker

Vertex AI

Weights & Biases

LangChain

LlamaIndex

OpenAI

Pinecone

Weaviate

By the numbers

400+

Engineers worldwide

200+

Active clients

20yr

Pure-play software

94%

Client retention

Engagement models

Three ways to hire AI & Data Engineers.

Scale your AI data capabilities with senior talent experienced in distributed computing, data warehousing, and model deployment.

01MOST POPULAR

Data & ML Engineering Pod

A cross-functional squad of data engineers, MLOps specialists, and backend developers delivering robust data architectures.

Production data pipelines
Feature stores & Lakehouse setup
Real-time streaming (Kafka/Flink)
Bi-weekly delivery demos

Deploy Data Pod

02EMBED

Hire AI & Data Engineers

Senior data and machine learning engineers embedded in your team to build pipelines that run in production — not just notebooks.

2-day talent shortlist
Senior Python, SQL & Spark pros
Time-zone aligned integration
Flexible monthly contracts

Request Engineer Profiles

03LAUNCH

Data Infrastructure Sprint

Modernize your data ingestion, transformation, and storage layer within 6–8 weeks with zero downtime for existing downstream consumers.

Fixed scope & timeline
Data governance & validation
CI/CD & automated testing
Complete documentation & handover

Start Data Sprint

FAQ

Asked first, every time.

Don't see yours here? Send us the question — a principal engineer will reply within 24 hours.

How quickly can you staff AI and data engineers?

Most teams are staffed within 1–2 weeks. We propose vetted profiles within 48 hours.

What AI/ML specialisations do your engineers cover?

ML engineering, data engineering, MLOps, computer vision, NLP/LLM, and GenAI (RAG, AI agents, prompt engineering).

Who owns the models and intellectual property?

You do. All models, code, pipelines, and documentation belong to you — full stop.

What is the difference between an AI engineer and a data engineer?

An AI engineer focuses on designing, training, and deploying machine learning models, whereas a data engineer focuses on building the data pipelines and infrastructure required to collect, clean, and store the data used by those models.

How do your MLOps engineers ensure model scalability in production?

Our MLOps engineers utilize containerization (Docker/Kubernetes), automated CI/CD pipelines, and robust monitoring tools to ensure that machine learning models can scale dynamically with user traffic while maintaining high inference speeds.

Can I hire ML engineers for a short-term specialized project?

Yes, we offer flexible engagement models. You can hire ML engineers on a project basis to solve specific challenges, or opt for dedicated AI staffing for long-term product development.

Do you provide dedicated AI staffing for long-term product development?

Absolutely. We specialize in providing dedicated AI staffing, seamlessly integrating our top-tier AI and data engineers into your internal teams for continuous, long-term enterprise development.

What technology stack do your data engineers specialize in?

Our data engineers are highly proficient in modern data stacks including Apache Spark, Kafka, Snowflake, Databricks, AWS Redshift, and Google BigQuery, ensuring robust ETL pipelines.

How do you evaluate the technical proficiency of your AI engineers?

We enforce a rigorous vetting process that includes advanced algorithm assessments, real-world system design interviews, and hands-on ML model deployment tasks before onboarding any AI engineer.

Can your data engineers help with migrating legacy data to a modern data lake?

Yes, we specialize in legacy modernization. Our data engineers can architect and execute a secure migration from legacy on-premise databases to scalable cloud data lakes without data loss.

Get AI engineers on your team this week.

Tell us about your project. We'll come back with a plan, a timeline, and the right team — no obligations.

Book a Call

AI & data engineers who ship models to production.

AI engineers who ship, not just experiment.

Production AI, Not Science Projects

Full-Stack Data Engineering

Your Team, Your Workflow

Case studies.

JobDroid

JobDroid

Fraud Detection Engine

Fraud Detection Engine

ML Engineering

Data Engineering

MLOps & Deployment

LLM & GenAI

Computer Vision

Analytics & BI

AI & Data Engineers: Our Proven Process

Scope

Match

Embed

Ship

Scale

Scope

Match

Embed

Ship

Scale

Why enterprises trust uswith their AI.

Higher automation rates

Measurable accuracy

Faster decision-making

Reduced operational cost

Production-grade reliability

Knowledge transfer

Tools our AI & Data EngineersDevelopersship with.

Data & ML Engineering Pod

Hire AI & Data Engineers

Data Infrastructure Sprint

Asked first, every time.

Related capabilities.

Vibe Coding

AI Agents

Custom MCP Development

Conversational AI

Get AI engineers on your team this week.

Why enterprises trust us
with their AI.

Tools our AI & Data Engineers
Developers
ship with.