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ML Engineer

Hire ML Engineer Developers

Pre-vetted senior ML engineers ready to join your team in 48 hours. Build and deploy production-grade machine learning models, MLOps pipelines, LLM-powered applications, computer vision systems, and NLP solutions with engineers who have shipped models running at scale in production.

35+
ML Engineers
6+ Yrs
Avg Experience
200+
Models Deployed
48hrs
Start Time

Get Your Custom Project Plan

Share your project details — a senior engineer responds within 4 hours.

🔒NDA Protected
24hr Response
💬Free Consultation
Why Codazz

Why Hire ML Engineer
Developers From Us.

Vetted ML Experts

Every ML engineer passes our 5-stage vetting: ML theory assessment, model-building challenge, MLOps pipeline review, live coding session, and reference checks. We verify real production experience — not just notebook tutorials. Only the top 3% qualify.

🤖

LLM & Generative AI Specialists

Our ML engineers have hands-on experience fine-tuning LLMs using LoRA, QLoRA, and RLHF. They build RAG pipelines, semantic search, AI agents, and custom Hugging Face Transformers deployments that power real product features.

🔁

MLOps & Production Pipelines

Our engineers build robust MLOps pipelines using MLflow, Kubeflow, DVC, and Airflow. They automate data versioning, model training, evaluation, A/B testing, and continuous deployment — turning experiments into reliable production systems.

👁️

Computer Vision & NLP

Our ML engineers deliver computer vision systems (YOLO, Detectron2, OpenCV) for object detection, segmentation, and OCR, as well as NLP pipelines for classification, NER, sentiment analysis, and multilingual semantic search.

Model Deployment & Optimization

Our engineers optimize models for production using ONNX, TensorRT, and quantization techniques. They deploy via TorchServe, BentoML, AWS SageMaker, and Vertex AI, achieving low-latency inference at scale.

💸

40-60% Cost Savings

Get senior ML engineers at a fraction of US in-house costs. No recruitment fees, no benefits overhead, no office space required. Engage for a specific ML project or embed long-term in your AI engineering team.

Available Talent

Meet Our
ML Engineer Developers.

ML1

Senior ML Engineer

6 years experience
Shipped 15+ models to production serving 1M+ daily requests
PythonPyTorchscikit-learnMLflowAWS SageMakerDocker
Available Now
ML2

LLM & GenAI Engineer

5 years experience
Fine-tuned and deployed LLaMA and Mistral for enterprise clients
PythonLangChainHugging FaceLoRARAGOpenAI API
Available Now
ML3

Computer Vision Engineer

7 years experience
Built real-time defect detection system for manufacturing (99.2% accuracy)
PythonPyTorchYOLOOpenCVTensorRTONNX
Available in 1 week
ML4

MLOps Engineer

6 years experience
Built end-to-end MLOps platform reducing model deployment time by 80%
KubeflowMLflowAirflowDVCKubernetesTerraform
Available Now
Engagement Models

Flexible Hiring
Models.

Most Popular

Full-Time Dedicated

40 hrs/week

A developer works exclusively on your project, fully embedded in your team and processes.

  • Dedicated resource
  • Daily standups
  • Sprint planning
  • Direct Slack/Teams access
Budget-Friendly

Part-Time Flexible

20 hrs/week

Consistent senior support without the full-time commitment. Ideal for startups and scaling teams.

  • Flexible scheduling
  • Async communication
  • Weekly sync calls
  • Progress reports
Enterprise

Team Augmentation

2-10 devs

Extend your existing engineering team with multiple developers who integrate into your workflow.

  • Team lead included
  • CI/CD integration
  • Code review process
  • Knowledge transfer
Defined Budget

Project-Based

Fixed Scope

A dedicated team for a defined project with clear milestones, timeline, and deliverables.

  • Fixed-price quote
  • Milestone payments
  • Project manager
  • Warranty included
Tech Expertise

ML Engineer
Tech Stack.

Languages & Frameworks

PythonPyTorchTensorFlowKerasJAXscikit-learn

LLMs & GenAI

Hugging FaceLangChainLlamaIndexOpenAI APILoRA / QLoRARAG Pipelines

MLOps & Pipelines

MLflowKubeflowDVCWeights & BiasesAirflowPrefect

Model Deployment

ONNXTensorRTTorchServeBentoMLAWS SageMakerVertex AI

Computer Vision

YOLODetectron2OpenCVTorchvisionAlbumentationsRoboflow

Data & Infrastructure

PandasSparkDaskRayPostgreSQLPinecone
Hiring Process

4 Simple Steps
To Your Team.

01

Share Requirements

Day 1

Tell us about your project, tech stack, and the type of developer you need. We will match you with the best-fit candidates from our vetted talent pool.

02

Interview Developers

Day 1-2

Interview pre-screened developers who match your requirements. Evaluate technical skills, communication, and culture fit on your own terms.

03

Onboard & Integrate

Day 2-3

Your selected developer signs the NDA, gets access to your tools, and joins your team channels. We handle all the logistics.

04

Start Building

Day 3+

Your developer is fully operational — writing code, attending standups, and shipping features. We provide ongoing support and performance management.

FAQ

Common
Questions.

You can interview pre-matched ML engineers within 24 hours of sharing your requirements. Onboarding typically completes within 48 hours. Our engineers are ready to start building models, MLOps pipelines, and AI-powered features immediately.

Our ML engineers are proficient in Python, PyTorch, TensorFlow, Keras, scikit-learn, Hugging Face Transformers, LangChain, and JAX. For MLOps they use MLflow, Kubeflow, DVC, Weights & Biases, and Airflow. For deployment they work with ONNX, TensorRT, TorchServe, and BentoML.

Yes. Our ML engineers have hands-on experience fine-tuning LLMs including GPT-4, LLaMA, Mistral, and Falcon using LoRA, QLoRA, and RLHF. They build RAG pipelines, custom embeddings, and production-ready LLM APIs that integrate seamlessly into your application.

Yes. Our ML engineers have shipped computer vision systems for object detection, image segmentation, OCR, and video analytics using YOLO, Detectron2, and OpenCV. For NLP they build text classification, sentiment analysis, named entity recognition, and semantic search systems.

Rates depend on seniority, the depth of ML and MLOps specialization you need, and whether the engagement is full-time, part-time, or team augmentation. Pricing is scoped to the specific role and engagement model once we understand your requirements, with no hidden fees, recruitment charges, or long-term lock-in.

Absolutely. We sign enforceable NDAs on Day 1 before any project discussion begins. Your models, datasets, training pipelines, and business logic are fully protected from the first conversation.

Ready to Hire ML Engineer Developers?

Share your requirements. We will match you with pre-vetted ml engineer developers within 24 hours.

Get Your Custom Project Plan

Share your project details — a senior engineer responds within 4 hours.

🔒NDA Protected
24hr Response
💬Free Consultation