1.400+ ML Engineers verfügbar

Machine Learning
Engineers finden

Engagieren Sie geprüfte TensorFlow-, PyTorch- und Scikit-learn-Experten in nur 48 Stunden. Von NLP bis Computer Vision: Finden Sie ML Engineers, die produktionsreife Modelle ausliefern.

48 hrs

Zeit bis zum Match

Top 3%

Aufnahmequote

150+

Länder

ML Engineers finden So funktioniert’s

Elena K.

Senior ML Engineer

4.9 (94 Bewertungen)

PyTorch NLP LLMs

Raj M.

Computer Vision Specialist

5 (71 Bewertungen)

TensorFlow OpenCV

Amara J.

MLOps Engineer

4.8 (118 Bewertungen)

MLflow Kubernetes AWS SageMaker

Vertrauen führender Unternehmen

ML Technologies

Every Framework. Every Model.
One Platform.

Access machine learning engineers skilled in the complete ML ecosystem — from deep learning frameworks to production deployment.

Python

1,400+ devs

TensorFlow

890+ devs

PyTorch

920+ devs

Scikit-learn

1,100+ devs

Hugging Face

560+ devs

MLflow

420+ devs

Keras OpenCV spaCy LangChain CUDA NumPy Pandas Apache Spark AWS SageMaker Vertex AI Kubeflow DVC

Need a specialist in a specific ML domain?

Teilen Sie uns Ihre Anforderungen mit

Einfacher Prozess

How to Find Your ML Engineer

From requirements to matched talent in as little as 48 hours. Our AI + human approach ensures you get exactly the right fit.

Share Your Requirements

Tell us about your machine learning project — model types, data pipelines, deployment needs, and timeline. Our AI analyzes your requirements against 1,400+ ML engineer profiles.

Technical stack matching
Domain expertise filtering
Timezone & availability

Review Matched Candidates

Within 48 hours, receive a curated shortlist of pre-vetted ML engineers. Each candidate includes detailed profiles, research publications, and verified project histories.

3-5 matched candidates
Technical deep-dives
Model portfolio & papers

Start Building Together

Interview your top picks and onboard seamlessly. WorkGenius handles contracts, payments, and compliance across 150+ countries so you can focus on shipping models.

Compliant contracts
Global payments handled
Ongoing support

Ready to find your ML engineer?

Schedule a free consultation and get matched within 48 hours.

Gespräch vereinbaren

ML Projects

What Can ML Engineers Build?

From predictive analytics to generative AI, our engineers deliver production-ready machine learning solutions.

Predictive Models

Build accurate forecasting and classification models for demand prediction, churn analysis, fraud detection, and risk assessment.

Scikit-learnXGBoostTime Series

NLP Solutions

Develop text analysis systems including sentiment analysis, entity extraction, document classification, and conversational AI.

spaCyTransformersBERT

Computer Vision

Create image and video processing systems for object detection, facial recognition, medical imaging, and quality inspection.

OpenCVYOLOCNNs

Recommendation Systems

Design personalization engines for product recommendations, content discovery, and user matching using collaborative and content-based filtering.

EmbeddingsMatrix FactorizationDeep Learning

LLM Integration

Integrate and fine-tune large language models for chatbots, content generation, code assistance, and knowledge retrieval systems.

GPTLangChainRAG

MLOps & Deployment

Build end-to-end ML pipelines with automated training, versioning, monitoring, and scalable model serving infrastructure.

MLflowKubeflowSageMaker

Have a specific ML project in mind?

Projekt anfragen

Warum WorkGenius

Not Just Another
Freelance Marketplace

Traditional platforms give you thousands of profiles to sift through. WorkGenius gives you 3-5 perfect matches — pre-vetted ML engineers who fit your exact needs.

AI + Human Expertise

Our AI analyzes technical requirements while expert recruiters assess research depth and production experience.

Pre-Vetted Quality

Only the top 3% of applicants pass our technical assessments, ML system design reviews, and background checks.

Enterprise Compliance

Compliant hiring in 150+ countries. We handle contracts, payments, taxes, and legal requirements.

Starten Sie noch heute

Kostenlose Beratung. Keine Verpflichtung.

48hrs

Average time to first match

1,400+

Pre-vetted ML engineers

98%

Client satisfaction rate

150+

Countries supported

Häufige Fragen

ML Engineer Hiring FAQ

How quickly can I hire a machine learning engineer?

With WorkGenius, you can receive matched ML engineer candidates within 48 hours. Our AI-powered matching combined with human expertise ensures you get pre-vetted talent that matches your exact requirements. From initial consultation to engineer onboarding, most clients complete the hiring process within 1-2 weeks.

What ML technologies do your engineers specialize in?

Our network includes 1,400+ pre-vetted ML engineers specializing in:

Deep Learning: TensorFlow, PyTorch, Keras, JAX
Classical ML: Scikit-learn, XGBoost, LightGBM, CatBoost
NLP: Hugging Face Transformers, spaCy, LangChain, OpenAI API
Computer Vision: OpenCV, YOLO, Detectron2, MediaPipe
MLOps: MLflow, Kubeflow, DVC, Weights & Biases
Cloud ML: AWS SageMaker, Google Vertex AI, Azure ML

How are machine learning engineers vetted?

Every ML engineer goes through a rigorous multi-step vetting process:

Application Review: Resume, research publications, and project portfolio assessment
Technical Assessment: ML algorithm implementation, data processing, and model evaluation challenges
Live Coding Interview: Real-time ML problem-solving with senior ML engineers
System Design Review: ML architecture, scalability, and production deployment evaluation
Background Verification: Identity and professional reference checks

Only the top 3% of applicants make it into our network.

What does it cost to hire a machine learning engineer?

Rates vary based on experience level, specialization, and location. Typical ranges:

Junior ML Engineer: $50-80/hour
Mid-Level ML Engineer: $80-130/hour
Senior ML Engineer: $130-180/hour
ML Architect/Principal: $180-250+/hour

WorkGenius provides transparent pricing with no hidden fees. We handle all payments, taxes, and compliance.

What's the difference between an ML engineer and a data scientist?

While there's overlap, the roles have distinct focuses:

ML Engineers: Focus on building, deploying, and scaling production ML systems. They write robust, maintainable code and handle MLOps.
Data Scientists: Focus on analysis, experimentation, and prototyping. They explore data, test hypotheses, and develop initial models.

If you need models in production at scale, hire an ML engineer. If you need data exploration and insights, consider a data scientist. Many projects benefit from both.

What if the ML engineer isn't the right fit?

We stand behind our matching quality with a replacement guarantee. If an engineer doesn't meet your expectations within the first two weeks, we'll provide a replacement at no additional cost. Our 98% client satisfaction rate reflects our commitment to finding the right fit the first time.

Noch Fragen? Sprechen wir darüber.