Software Engineering & Digital Products for Global Enterprises since 2006
CMMi Level 3SOC 2ISO 27001
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Embed senior engineers in your team within weeks.
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A ring-fenced squad with PM, leads, and engineers.
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We hire, run, and transfer the team to you.
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Try the talent. Convert when you're ready.
ForceHQ
Skill testing, interviews and ranking — powered by AI.
RoboRingo
Build, deploy and monitor voice agents without code.
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Policy, retention and compliance for enterprise email.
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Test and train staff against AI-driven voice attacks.
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Continuous, adaptive security training for every team.
IDS Load Balancer
Built for Multi Instance InDesign Server, to distribute jobs.
AutoVAPT.ai
AI agent for continuous, automated vulnerability and penetration testing.
Salesforce + InDesign Connector
Bridge Salesforce data into InDesign to design print catalogues at scale.
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Cloud, digital and legacy modernisation across financial entities.
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Clinical platforms, patient engagement, and connected medical devices.
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Trial systems, regulatory data, and field-force enablement.
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Workflow automation, learning platforms, and consulting tooling.
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AI video processing, OTT platforms, and content workflows.
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Product engineering, integrations, and scale for tech companies.
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Shopify, print catalogues, web-to-print, and order automation.
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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
8+
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.
Trusted by enterprises worldwideCMMi Level 3ISO 27001SOC 220+ Years
Why MetaDesign

AI engineers who ship, not just experiment.

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

01

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.

02

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.

03

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.

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

Five stages, paired end-to-end.

Predictable delivery. No black-box sprints.

01

Scope

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

02

Match

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

03

Embed

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

04

Ship

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

05

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.

Technology

Tools our ai & data engineersdevelopers ship with.

We use what works. No vendor lock-in.

PyTorchTensorFlowscikit-learnXGBoostHugging FaceSnowflakeBigQueryDatabricksdbtAirflowMLflowSageMakerVertex AIWeights & BiasesLangChainLlamaIndexOpenAIPineconeWeaviate
By the numbers
400+
Engineers worldwide
200+
Active clients
20yr
Pure-play software
94%
Client retention
Engagement models

Three ways to work with our AI & Data Engineers team.

Scale up, scale down — zero procurement headaches.

Fixed-scope project

Start-to-finish delivery with total cost, timeline, and scope agreed upfront. Best for well-defined builds and launches.

BEST FORNew product launches

Dedicated team

A ring-fenced squad — PM, tech lead, engineers, QA — fully managed by us, embedded in your workflow.

BEST FORLong-running platforms

Staff augmentation

Plug senior engineers into your existing team and tools. You manage priorities, we deliver results.

BEST FORCapacity gaps & sprints
FAQ

Asked first, every time.

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

Most teams are staffed within 1–2 weeks. We propose vetted engineer profiles within 48 hours of receiving your requirements. For niche skills like computer vision or NLP, we may need 2–3 weeks.

ML engineering (PyTorch, TensorFlow), data engineering (Snowflake, Databricks, dbt), MLOps (MLflow, SageMaker), computer vision (YOLO, Detectron2), NLP/LLM (LangChain, fine-tuning), and GenAI (RAG, AI agents, prompt engineering).

Yes. We embed into your existing stack — SageMaker, Vertex AI, Databricks, custom Kubernetes clusters. Your tools, your data, your workflow.

Both. Our engineers build the full stack — data pipelines, feature stores, model training, deployment, and monitoring. No handoff gaps between data and ML teams.

Every model ships with monitoring dashboards, drift detection, automated retraining triggers, and A/B serving infrastructure. We track precision, recall, latency, and business metrics — not just offline accuracy.

Yes. We have engineers experienced with OpenAI, Gemini, Claude, Llama, and Mistral — building RAG pipelines with vector databases (Pinecone, Weaviate), prompt engineering, guardrails, and evaluation frameworks.

You do. All models, code, pipelines, and documentation belong to you — full stop. We provide complete repository access and handover documentation.

We offer a replacement guarantee. If the engineer doesn't meet your expectations within the first 2 weeks, we replace them at no additional cost.

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