ML DEVELOPERS

Hire ML Developers to Deploy Machine
Learning Systems

Cypherox provides machine learning developers who train models, build prediction pipelines and integrate ML into production systems so your product learns from data.

Engineering partner, not a staffing agency
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SECURITY AND TRUST

Built for Confidential,
Production Work

Every engagement starts with a signed NDA and a clear data handling agreement, so your training data, models and predictions stay protected throughout development and beyond.

Confidentiality protected at every stage.

Signed NDA Agreements

Every project begins under a mutual non-disclosure agreement before any code or training data changes hands.

Secure Development Practices

Access to data repositories, model training infrastructure and production systems is controlled and limited to the engineers assigned to your project.

Data Handling Controls

Training data, model weights and API keys are handled under agreed protocols and never shared beyond the delivery team.

IP Ownership Clarity

Code, models and documentation produced during the engagement belong to you, not to Cypherox.

PRE-VETTED TALENT

Hire Pre-Vetted Developers for Your Team

We screen every developer for ML depth, data-handling discipline and production deployment experience before matching them to your project.

Alex

Senior iOS Developer

Available Now

Builds production-grade iOS apps with clean architecture, reactive Combine pipelines and smooth UI animations. Experienced with UK startups & enterprise platforms.

Skills:

SwiftSwiftUIUIKitCombine CoreDataREST APIs

Sarah

Lead iOS & Mobile Architect

Available Now

Specializes in modular VIPER and Composable Architecture (TCA), ARKit features, biometric security and enterprise CI/CD test automation.

Skills:

SwiftObjective-CTCAARKit XCTestFastlane

David

Senior iOS & API Engineer

Available Now

Focuses on offline-first database sync, real-time WebSocket feeds, Apple Pay integrations and backend API orchestration for consumer apps.

Skills:

SwiftSwiftUICoreDataWebSockets FirebaseGraphQL
PROVEN DELIVERY

ML Delivery That
Turns Data Into Value

A look at how dedicated ML developers have supported model building, pipeline automation and production deployment across different product environments.

Infrastructure Automation

Automating Deployment Across Environments

Challenge: A product team deployed manually to staging and production, creating inconsistent environments and slow release cycles that blocked feature delivery.
Solution: DevOps developers built infrastructure as code using Terraform, standardized container deployment with Docker and Kubernetes and created repeatable deployment processes across all environments.
60%
Reduction in deployment time
95%
deployment success rate
8★
releases per week vs 1
Next-Gen Mobile Banking & Wealth Platform
PRICING MODELS

Hire ML Developers on Terms
That Fit Your Project

Choose the engagement model that fits your timeline, budget and how much control you want over day-to-day delivery.

Hourly Hiring

$24 /Hour

Bring in an ML developer for specific model work, data analysis, or proof of concept work without a long-term commitment.

  • Pay only for hours worked
  • No minimum monthly commitment
  • Scale up or down as needed
  • Fast to start
Start Hourly

Dedicated Monthly

$3,400 /Month

An ML developer works exclusively on your ML systems every month, integrated into your team and delivery cycle.

  • Full-time focus on your ML work
  • Consistent developer across sprints
  • Direct communication with your team
  • Predictable monthly cost
Go Dedicated

Fixed Cost Solution

Custom Quote

A defined scope, timeline and cost agreed upfront, suited to ML projects with clear requirements and measurable outcomes.

  • Scope agreed before work begins
  • Cost certainty from the outset
  • Milestone-based delivery
  • Fits well-defined projects
Request a Quote
Compare Hiring Models →

Get Started

Share a few details about your ML requirements, the type of model work needed and your timeline and we will follow up to discuss next steps.

OUR TECHNOLOGY

The Technology Behind
Our ML Developers

ML developers work across established ML frameworks, data tools and production patterns suited to real-world systems.

INDUSTRY USE

ML Support Across Different Industries

The right ML developer depends on your data volume, prediction latency and how critical accuracy is to your business.

Financial Services and Credit Risk

Finance teams need ML developers who assess credit risk and detect fraud using transaction and applicant data.

  • Scores loan applications for approval probability.
  • Detects fraudulent transactions in real time.
  • Monitors model performance and bias.

Retail and Demand Forecasting

Retail teams need ML developers who forecast demand so inventory and pricing match customer behavior.

  • Forecasts demand by product and store.
  • Optimizes pricing based on elasticity.
  • Recommends inventory levels.

Healthcare and Diagnosis

Healthcare teams need ML developers who assist diagnosis using patient data and imaging while maintaining regulatory compliance.

  • Screens medical images for abnormalities.
  • Predicts patient readmission risk.
  • Identifies high-risk patient populations.

Marketing and Personalization

Marketing teams need ML developers who personalize customer experience and predict which channels work best.

  • Predicts customer lifetime value.
  • Recommends products to individual users.
  • Optimizes campaign targeting.
CLIENT FEEDBACK

What Our
Clients Say

Feedback from teams who have worked with Cypherox ML developers on real projects, across different engagement models.

WHY CYPHEROX

Why Teams Choose Cypherox ML Developers

ML developers are positioned as delivery capacity within your engineering process, not as a separate research function.

11
+
Years of Experience
80
+
Experienced Developer Team
99
%
Client Satisfaction and long-term contract retention
48
h
Average Onboarding Time from interview to first commit
COMMON QUESTIONS

Hire ML Developer
Questions

These are the questions we hear most often from teams evaluating an ML developer hire, covering data, models, accuracy and production deployment.

Still have questions? Talk to Us

This depends on the problem complexity and prediction accuracy needed. ML developers can estimate data needs and work with what you have to build effective models.

Simple models can go live in weeks. Complex models with new data collection take months. ML developers break work into milestones so value arrives progressively.

Define success metrics first, then measure the model against them. Accuracy, precision and recall all matter depending on your use case. ML developers help set realistic targets.

Model monitoring detects accuracy drift, triggering retraining with fresh data. ML developers build this monitoring into the system so issues surface early.

Open source models are faster to deploy. Custom models suit problems where your data gives competitive advantage. ML developers evaluate both approaches.

Test models for bias across demographic groups, monitor predictions for disparate impact and retrain when bias emerges. ML developers build fairness checks into pipelines.

ML developers can continue on an ongoing basis for model retraining, new features, or pipeline improvements, using the same hourly, dedicated, or fixed cost models available from the start.