Hire Senior
AI & ML Developers

Looking to hire AI developers or machine learning engineers without agency overhead? You've found the team. Whether you need to hire ML engineers for model development, hire AI developers for LLM integration, or hire machine learning engineers for production MLOps — our roster covers the full AI stack. 45+ combined years across LLMs, computer vision, NLP, reinforcement learning, and agentic systems. Shipped across 8 domains.

  • LLMs, computer vision, NLP, RL & agentic AI — research to production
  • European base — US & AU timezone overlap
  • First working deliverable in 1 week — no PoC theatre, no ramp-up delay
45 yrs
Years combined AI & Python experience
8
AI domains shipped to production
7+
ML & LLM frameworks in production
US & AU
Timezones overlap
1 week
To first working deliverable

Let's Solve
Your Bottleneck

Real track record in FinTech, Healthcare, E-commerce, Supply Chain and SaaS AI. Book a 15-min intro call — tell us what you're building.

Book a Discovery Call

Technical Stack

Core ML
Python PyTorch TensorFlow Scikit-learn NumPy Pandas Jupyter Matplotlib Seaborn
LLMs & NLP
LangChain HuggingFace OpenAI / GPT-4 Anthropic API BERT Transformers spaCy NLTK Deepgram RAG
Computer Vision
OpenCV YOLOv5 / YOLO CNN / RNN Real-time video pipelines Face recognition Object detection
MLOps & Infra
FastAPI Django Docker Kubernetes AWS AWS EKS PostgreSQL MongoDB RabbitMQ Redis Airflow CI/CD
Data & Analytics
SQL Tableau Power BI LSTM Gradient Boosting Time Series Bayesian Optimization

Domain Experience

🤖
LLM & Agentic AI
Production LLM pipelines, RAG systems, autonomous agents, voice AI, conversational bots. GPT-4, Anthropic, Deepgram, LangChain.
👁
Computer Vision
YOLO object detection, real-time facial recognition, foot traffic analytics, PPE safety monitoring, movement recognition.
💬
NLP & Text Analytics
Sentiment analysis, topic modeling, document processing pipelines, BERT-based classification, 100K+ documents/month at scale.
📈
Predictive Analytics
Time series forecasting with LSTM, demand prediction, churn models at 87% accuracy, gradient boosting, Bayesian optimization.
💳
FinTech AI
Financial indicator prediction, ML-driven ad revenue (+$2M), churn prevention, behavioral analytics, algorithmic trading signals.
🏥
Healthcare & MedTech
Movement recognition for physiotherapy, posture analysis, exercise form AI, patient data modeling, medical computer vision.
🏭
Supply Chain & Ops
Reinforcement learning for inventory optimization, –23% waste reduction, demand forecasting, stock availability improvement.
⚙️
MLOps & AI Infra
End-to-end ML pipelines from research to production, Kubernetes deployment, AWS EKS, CI/CD for model delivery, monitoring.

Projects

01
LLM-Powered Web Scraping Platform
AI Infrastructure · Open-source + SaaS
Production LLM pipeline processing thousands of web pages daily with 95%+ accuracy. GPT-4 with custom prompt engineering for dynamic website structures. Open-sourced; significant GitHub community adoption.
PythonGPT-4LangChain FastAPIPrompt EngineeringAWS
02
Inventory Optimization with Reinforcement Learning
Supply Chain · Retail logistics startup
RL algorithms for intelligent inventory management reducing waste by 23%. Bayesian optimization for demand forecasting achieving 18% improvement in prediction accuracy. End-to-end LSTM time series pipeline from data ingestion to production scheduling.
PyTorchRL (PPO/DDPG)LSTM Bayesian OptimizationPythonAWS
03
Content Scoring NLP Model
E-commerce · Major European marketplace
NLP-driven content scoring model increasing ad revenue by 15% (~$2M annual impact). Unsupervised topic modeling for content categorization (+12% accuracy). RL-based personalization and exploration strategies for website recommendations.
PythonBERTScikit-learn NLPTensorFlowRL
04
Real-Time Computer Vision Foot Traffic System
Smart Cities · Public transport analytics
People counting and facial recognition system for real-time video streams in public transportation. OpenCV-based face recognition microservices integrated into Django. Data pipelines for large-scale camera feeds with real-time alerts and historical reporting.
PythonOpenCVDjango PostgreSQLAWS EKSKubernetes
05
AI-Powered Support Automation SaaS
SaaS · Enterprise support automation
Full-stack development of an AI-driven SaaS platform for support department automation. Prompt engineering, master prompt design for monitoring console, AI training modules, backend services for AI integration, and DevOps for cloud infrastructure.
PythonFastAPIDjango Prompt EngineeringDockerKubernetesAWS
06
Voice AI Conversational System
Voice AI · Seed-funded startup
Production voice AI integrating state-of-the-art TTS with GPT-based dialogue management. Built as CTO — secured seed funding, managed cross-functional ML team. Speech generation models and LLM-powered conversational agents.
PythonGPTTTS Models LangChainSpeech GenerationAWS
07
Agentic Psychological Support System
Healthcare AI · Behavioral analytics platform
RAG-based agentic voice chat for psychological support with behavioral analytics. Implemented agentic voice interactions using LangChain and Deepgram, real-time behavioral pattern analysis and agent-powered support conversations.
LangChainAnthropic APIDeepgram RAGFastAPIPython
08
FinTech Churn Prediction & Financial Forecasting
FinTech · Real-time financial intelligence platform
Real-time financial indicator prediction with advanced LSTM time series. Churn model with 87% accuracy using gradient boosted decision trees. Large-scale NLP pipeline processing 100K+ financial documents monthly. Interactive dashboards for business analysts.
PythonTensorFlowScikit-learn LSTMGradient BoostingPandasSQL

Why Our Team

Typical offshore / agency DMexec
Research depth Off-the-shelf API wrappers. No custom model training or fine-tuning capability.
Published RL research. Custom training, fine-tuning and novel architecture from scratch.
LLM expertise ChatGPT wrapper integrations. Hallucination-prone, no production hardening.
Production LLM pipelines with 95%+ accuracy. Custom prompt engineering, RAG, agents — not just OpenAI API calls.
Computer Vision Not available in most ML teams. Requires a specialist hire or separate agency.
OpenCV, YOLOv5, real-time video processing in production — foot traffic, facial recognition, PPE monitoring already shipped.
MLOps PoC models that never reach production. No pipeline from experiment to deployment.
Full pipeline from research to Kubernetes-deployed production — Docker, AWS EKS, CI/CD, monitoring baked in.
Business impact Accuracy benchmarks. No clear link between model performance and revenue.
+$2M ad revenue uplift. –23% supply chain waste reduction. 87% churn prediction accuracy. Business outcomes, not just benchmarks.
Hiring cost Recruiter fees 15–25% of salary plus agency markup 40–80%. Weeks before first output.
$0 recruiting cost. Direct engagement — no agency markup, no recruiter cut.
Time to deliver 4–6 week PoC before seeing anything. Data gathering, "discovery" and alignment sprints delay output.
Working prototype or first model in 1 week. No PoC theatre — we ship fast, then iterate.

FAQ

We cover the full AI development lifecycle: custom ML model development, LLM integration and fine-tuning, computer vision systems, NLP pipelines, predictive analytics, MLOps infrastructure, and agentic AI systems. Whether you need to hire AI developers for a greenfield build or hire machine learning engineers to augment your existing team — our roster handles both.

Yes. We build production-grade LLM pipelines — RAG architectures, custom prompt engineering, agentic workflows, fine-tuned models, and multi-model orchestration. Our team includes an LLM specialist who shipped a production scraping platform running at 95%+ accuracy. If you need to hire LLM developers who go beyond API calls, this is the right team.

Yes — deployed and running in production. We've built real-time people counting and facial recognition systems for public transport, YOLOv5 PPE detection for safety monitoring, movement recognition for healthcare applications, and custom object detection pipelines for industry automation. OpenCV, YOLO, CNN/RNN architectures — all in live production environments.

Fully. Our team spans model research and architecture, data pipeline engineering, backend integration via FastAPI and Django, cloud deployment on AWS with Kubernetes, and CI/CD for model versioning and retraining. You don't need to hire a separate ML team and a separate DevOps team — we bring both under one engagement.

FinTech, Healthcare & MedTech, E-commerce, Supply Chain & Logistics, Enterprise SaaS, Computer Vision & Safety, Voice AI, and Telecom. Real production projects — not proof-of-concept work. Industries where AI mistakes cost real money, which makes the team precise about what gets deployed.

First working deliverable within 1 week of contract signature — a working prototype, a running pipeline, or a model evaluation on your data. No four-week "discovery sprints," no data collection delay, no PoC theatre before we show you something real.

Core ML: Python, PyTorch, TensorFlow, Scikit-learn. LLMs: LangChain, HuggingFace, GPT-4, Anthropic API, BERT, Transformers, spaCy. Computer Vision: OpenCV, YOLOv5. MLOps: FastAPI, Django, Docker, Kubernetes, AWS, Airflow, RabbitMQ. Whether you need to hire ML engineers, hire AI developers, or hire data scientists — the full Python AI stack is covered.

Yes. Staff augmentation is one of our core models. Your codebase, your tooling, your sprint cadence — we embed directly. You can also engage us for end-to-end AI delivery or consulting. The model is flexible; the engineers are the same regardless of engagement type.

Fixed monthly rate per engineer — no recruiter fees, no payroll taxes, no equipment costs. Rates vary by seniority and AI specialization (LLM, CV, MLOps). Reach out and we'll give you a straight number within 24 hours.

Most AI agencies sell you PoCs that never reach production, or wrap existing APIs and call it ML. Our team has published RL research, measurable business outcomes: +$2M ad revenue uplift, –23% supply chain waste reduction, 87% churn accuracy in FinTech. We ship, and we can demonstrate exactly what shipped and what it delivered.

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