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We know the technology.
Not just the terminology.

Most recruiters learn to spell the words. Our team learns the concepts. That domain literacy is what lets us distinguish a genuinely skilled ML engineer from someone who lists TensorFlow on their CV.

Our Expertise

Six domains we hire for with real depth

Our recruiters hold focused domain knowledge built through genuine immersion in the technology community. They attend developer events, read engineering blogs, and understand what separates junior from senior — not just in title, but in capability.

🤖
Generative AI & LLMs
The most in-demand domain of the decade
🧠
Machine Learning
Core ML, MLOps, NLP, Computer Vision
📊
Data Engineering
Pipelines, lakehouses, analytics
☁️
Cloud & DevOps
AWS, GCP, Azure, Kubernetes, SRE
Highest Demand

Generative AI & Large Language Models

The fastest-growing hiring segment in technology. We understand the architectural differences between RAG, fine-tuning, and prompt engineering approaches — and we screen accordingly. Our network includes practitioners who've shipped production GenAI systems, not just experimenters.

LLM EngineerPrompt EngineerRAG SpecialistGenAI ArchitectAI Product EngineerFoundation Model Researcher
Common tools
OpenAI / Anthropic APIs
LangChain / LlamaIndex
Hugging Face Transformers
Vector DBs (Pinecone, Weaviate)
Fine-tuning (LoRA, QLoRA)
Core AI

Machine Learning & MLOps

We hire across the full ML spectrum — from research scientists building novel architectures to MLOps engineers ensuring models run reliably in production. We evaluate candidates on real engineering rigour, not just familiarity with popular frameworks.

ML EngineerData ScientistMLOps EngineerNLP EngineerComputer Vision EngineerResearch Scientist
Common tools
PyTorch / TensorFlow / JAX
Kubeflow / MLflow / DVC
SageMaker / Vertex AI
Feature stores, model registries
Data

Data Engineering & Analytics

The data infrastructure that powers AI and analytics products. We look for engineers who think about data quality, pipeline reliability, and lakehouse architecture — not just those who can write a Spark job from memory.

Data EngineerAnalytics EngineerData ArchitectPlatform Engineer (Data)dbt Developer
Common tools
Apache Spark / Flink / Kafka
dbt / Airflow / Prefect
Databricks / Snowflake
BigQuery / Redshift
Infrastructure

Cloud, DevOps & Platform Engineering

Infrastructure is a competitive advantage when done well. We hire cloud engineers and platform specialists who care about reliability, cost efficiency, and developer experience — building systems that scale with the product, not against it.

Cloud Engineer (AWS / GCP / Azure)DevOps EngineerPlatform EngineerSREKubernetes Engineer
Common tools
Kubernetes / Helm / ArgoCD
Terraform / Pulumi
GitHub Actions / Jenkins
Prometheus / Grafana
Product Engineering

Full-Stack Development

Engineers who can own the complete product — from building fast, accessible frontends to designing robust backend APIs and the databases that support them. We particularly value engineers who understand product context, not just implementation.

React / Next.jsNode.js / ExpressPython / FastAPIJava / Spring BootGoTypeScript
Common tools
React, Vue, Angular
PostgreSQL / MongoDB / Redis
GraphQL / REST / gRPC
Docker, CI/CD, testing frameworks
Emerging Tech

Frontier Technologies

We track the frontier and maintain a bench of specialists in technologies that are reshaping industries — from Blockchain and Web3 to IoT systems and spatial computing. These are rare skills, and finding the right people requires a different approach.

Blockchain / Web3 DevSmart Contract EngineerIoT EngineerAR / VR DeveloperEdge Computing
Common tools
Solidity / Rust / Move
Unity / Unreal / WebXR
MQTT / ROS
WASM / edge runtimes
Technology Index

Languages, frameworks & platforms we regularly hire for

🐍
Python
Language
Java
Language
🟦
TypeScript
Language
🦀
Rust / Go
Language
⚛️
React
Frontend
🟢
Node.js
Backend
🔶
AWS
Cloud
🔵
GCP
Cloud
🔥
PyTorch
ML Framework
🐳
Kubernetes
Infrastructure
Apache Spark
Data
🦜
LangChain
GenAI

Looking for niche technology talent?

Tell us the stack and the role. If we've placed someone in it before, we'll move fast. If it's new territory, we'll be honest about timelines.

Find specialist talent