MACHINE LEARNING TALENT

Hire Machine Learning Developers

Get pre-vetted Machine Learning developers deployed into your engineering team in 48-72 hours, with full onboarding completed in 2-3 weeks and a 7-day replacement SLA on every engagement.

    FREE CONSULTATION

    Pre-Vetted ML Profiles Fast

    Every Machine Learning developer is technically screened before deployment, so you interview a qualified shortlist, not raw applicants.

    Enterprise-Grade Deployment

    9Yards Technology backs every ML developer deployment with a written 7-day replacement SLA and a 95% client retention rate across 300+ engineer deployments.

    ABOUT US

    Machine Learning Engineering Talent at Enterprise Scale

    9Yards Technology is an IT staff augmentation company that has deployed 300+ pre-vetted engineers for enterprise clients across North America, the Middle East, and India. Our India engineering hub sources and deploys Machine Learning developers across TensorFlow, PyTorch, Scikit-learn, MLOps, and cloud AI platforms for product teams that need verified talent fast. We are measured on a 95% client retention rate and a 7-day replacement SLA, not on placement fees.

    hire ml developer
    1 +
    Project Delivered
    1 +
    Countries Served
    1 +
    Dynamic Experts
    1 +
    Glorious Years    
    OUR SERVICES

    Machine Learning Development Services for Enterprise Teams

    9Yards Technology delivers the full range of Machine Learning engineering capabilities enterprise product teams need, from predictive model development to production-grade MLOps and generative AI integration.

    Predictive Analytics Development

    Pre-vetted ML developers build and deploy predictive models that turn historical data into actionable business intelligence. Engineers work across regression, classification, and forecasting use cases at production scale.

    Deep Learning Model Engineering

    Dedicated ML developers design and train deep neural networks using TensorFlow and PyTorch for image recognition, speech processing, and complex sequence modelling. Every model is optimised for inference speed and deployment reliability.

    Natural Language Processing Solutions

    ML engineers build NLP pipelines covering entity recognition, sentiment analysis, text classification, and large language model integration for enterprise applications. Solutions are production-hardened and tested for accuracy before deployment.

    Computer Vision Engineering

    9Yards Technology deploys computer vision specialists who deliver object detection, image segmentation, and visual inspection systems for manufacturing, retail, and healthcare clients. Engineers use OpenCV, YOLO, and cloud vision APIs to production standards.

    MLOps and Pipeline Automation

    Offshore Machine Learning developers design and operate end-to-end MLOps pipelines covering model versioning, automated retraining, monitoring, and CI/CD integration on AWS, Azure, and GCP. Scalable infrastructure reduces model drift and keeps production systems reliable.

    Generative AI and LLM Integration

    Dedicated ML developers integrate generative AI capabilities including LLM fine-tuning, retrieval-augmented generation, and custom AI assistant development into existing enterprise platforms. Engagements include security review and data governance aligned to client compliance requirements.

    WHY CHOOSE US?

    Why Enterprises Hire ML Developers With 9Yards Technology

    Enterprise engineering leaders choose 9Yards Technology because every Machine Learning deployment is backed by a written 7-day replacement SLA and a 95% client retention rate that most staffing partners do not publish.

    Profiles in 48-72 Hours
    Pre-vetted Machine Learning developer profiles arrive within 48-72 hours of your requirement submission. The traditional hiring market averages 90 days for a comparable senior ML role.
    Written 7-Day Replacement SLA
    If a deployed ML developer underperforms in the first weeks, 9Yards Technology replaces them within 7 days at no renegotiation cost. The replacement SLA is in writing before the contract is signed.
    95% Client Retention Rate
    A 95% client retention rate across 300+ engineer deployments is independently verifiable proof of delivery quality. Industry average retention for staffing engagements sits at approximately 70%.
    Cost-Optimized Senior ML Talent
    Senior AI/ML engineers deployed through 9Yards Technology cost $45,000-$60,000 annually versus $180,000-$220,000 for US local equivalents, delivering verified annual savings of $120,000-$160,000 per senior hire.
    Enterprise-Grade Governance
    Every ML engagement includes 100% NDA adherence, structured compliance processes, transparent reporting, and dedicated account management built specifically around staffing continuity, not a generalist service line.
    Full Deployment in 2-3 Weeks
    From requirement submission to a contributing Machine Learning developer on your team takes 2-3 weeks through 9Yards Technology's Talent Deployment Matrix, compared to a 90-day traditional hiring cycle.
    BUSINESS IMPACT OF ML

    What Dedicated ML Developers Deliver for Your Business

    Enterprise product teams that deploy Machine Learning developers through 9Yards Technology eliminate the 90-day hiring cycle and begin contributing to sprints from week one. Pre-vetted engineers across TensorFlow, PyTorch, MLOps, and cloud AI platforms accelerate intelligent feature delivery without adding hiring risk. With a 7-day replacement SLA and 95% client retention across 300+ deployments, you gain ML velocity backed by an enforceable quality guarantee.

    Faster Time to Model
    Pre-vetted ML developers contributing from week one compress the typical cold-hire ramp-up period and accelerate your first production model delivery significantly.
    Reduced Talent Acquisition Cost
    Senior AI/ML engineers deployed from India deliver annual savings of $120,000-$160,000 per role compared to US local equivalents, freeing budget for product investment.
    Lower Hiring Risk
    The written 7-day replacement SLA removes the single biggest fear enterprise teams have about offshore ML hiring: deploying an engineer who cannot deliver at the required level.
    Scalable ML Team Capacity
    9Yards Technology's India engineering hub scales your Machine Learning team up or down through flexible engagement models without the fixed overhead of permanent headcount.
    Production-Ready ML Pipelines
    Deployed engineers bring MLOps expertise in model versioning, automated retraining, and CI/CD integration, so ML systems stay reliable in production long after initial deployment.
    Seamless North America Collaboration
    ML developers deployed through 9Yards Technology are structured for time-zone overlap and async communication with US and Canada-based teams, enabling real sprint participation from day one.
    INDUSTRIES WE SERVE

    Machine Learning Development Across Diverse Industry Verticals

    9Yards Technology provides experienced Machine Learning engineers for enterprise projects across industries including BFSI, SaaS, Healthcare, Retail, Telecom, Manufacturing, Logistics, and eCommerce. Our developers understand not only the technology stack but also the business processes, compliance requirements, scalability challenges, and user expectations unique to each sector.
    Manufacturing Industrial Automation Energy & Utilities Telecom BFSI Retail Healthcare Government
    Read more
    ENGAGEMENT MODELS

    Flexible Hiring Models for Machine Learning Teams

    9Yards Technology offers five engagement models for hiring dedicated ML developers, covering everything from sprint-level agile delivery to long-term India engineering hub builds. Every model is backed by the same 48-72 hour profile SLA, 2-3 week deployment timeline, and written 7-day replacement guarantee. The right model depends on your roadmap certainty, team size, and whether you want eventual internal ownership of the deployed team.

    Time & Material (T&M)
    1
    Time and Material engagements give your Machine Learning team the flexibility to expand or contract scope sprint by sprint, ideal for AI projects where requirements shift as model performance data comes in. You pay for verified delivery hours, not a fixed scope that locks you into an early assumption.
    Fixed Price (FP)
    2
    Fixed Price engagements suit well-defined Machine Learning projects with a clear deliverable, a known dataset, and a measurable success metric. 9Yards Technology scopes, prices, and delivers against a defined outcome, giving your procurement team budget certainty before work begins.
    Dedicated Teams
    3
    Dedicated Teams give you a named group of pre-vetted Machine Learning developers who function as an extension of your internal engineering organisation, operating in your tools, attending your standups, and owning your ML roadmap long-term. This is the right model when you need consistent capacity rather than project-level bursts.
    Managed Services
    4
    Managed Services engagements hand off an entire ML function, such as model monitoring, retraining pipelines, or data engineering, to 9Yards Technology under a defined SLA. You receive governed, outcome-focused delivery with transparent reporting, not just headcount.
    Build-Operate-Transfer (BOT)
    5
    Build-Operate-Transfer gives companies establishing an India Machine Learning hub a structured path from zero to a fully operational, internally owned team. 9Yards Technology builds and operates the team under its own governance for an agreed period, then transfers full ownership to the client's rolls after 12 months.
    Our Tech Stack

    Expertise Across Modern Technologies

    Languages, frameworks, and libraries used to build application logic on both server and client.

    • Back End

      • c++ C++
      • nestjs NestJS
      • flask Flask
      • django Django
      • express js Express.js
      • dot net .NET
      • php PHP
      • ruby Ruby
      • java spring Java Spring
      • python Python
    • Front End

      • open cv OpenCV
      • next js Next.js
      • svelte Svelte
      • vue js Vue.js
      • angular Angular
      • react js React.js
      • progressive web apps PWA
      • type script TypeScript
      • javascript JavaScript 
      • html/css HTML/CSS

    Deployment, observability, and data storage systems that power the platform behind the scenes.

    • DevOps & Cloud

      • conan Conan
      • cmake Cmake
      • github actions Github Actions
      • cuda CUDA
      • datadog Datadog
      • grafana Grafana
      • kubernetes Kubernetes
      • podman Podman
      • docker Docker
      • google cloud Google Cloud
    • Database Development

      • mariadb MariaDB
      • redis Redis
      • cassandra Cassandra
      • mongodb MongoDB
      • oracle Oracle DB
      • sql server SQL Server
      • postgresql PostgreSQL
      • elasticsearch Elasticsearch
      • mysql MySQL

    Blockchain tooling and AI/ML frameworks used for next-generation, intelligent, and decentralized features.

    • Web 3

      • evm EVM
      • arbitrum Arbitrum
      • nownodes NOWNodes
      • web3js Web3.js
      • hardhat Hardhat
      • ethers Ethers.js
      • openzeppelin OpenZeppelin
      • chainlink Chainlink
      • truffle Truffle
      • moralis Moralis
    • Artificial Intelligence

      • dl4j DL4J
      • chainer Chainer
      • opencv OpenCV
      • cntk CNTK
      • caffe Caffe
      • theano Theano

    Enterprise platforms and quality-assurance tooling used for integrations, automation, and testing.

    • Trending Platforms

      • dynamics365 Dynamics365
      • power bi Power BI
      • sharepoint SharePoint
      • servicenow ServiceNow
      • salesforce Salesforce
      • sap SAP
      • adobe commerce Adobe Commerce
    • Testing Tools

      • apache jmeter Apache JMeter
      • appium Appium
      • cuit CUIT
      • fmbt fMBT
      • hq quick test professional HP Quick Test Professional
      • postman Postman
      • protractor Protractor
      • ranorex Ranorex
      • selenium Selenium
      • testtrack TestStack.White
      • tsung Tsung
      • unified functional testing Unified Functional Testing
      • warp Warp
      • xctest XCTest
    MACHINE LEARNING STAFFING

    Our Differentiator!

    Most staffing agencies optimise for placement fees, not candidate quality. 9Yards Technology’s 7-day replacement SLA is a public bet on our own vetting process: if a deployed Machine Learning developer does not meet your bar in the first weeks, we replace them within 7 days at no renegotiation cost. That guarantee is in writing before the contract is signed, not offered as a verbal reassurance after a problem surfaces.

    The traditional US hiring market averages 90 days to fill a senior Machine Learning role. 9Yards Technology’s Talent Deployment Matrix delivers pre-vetted ML developer profiles in 48-72 hours and completes full deployment within 2-3 weeks. Speed is possible because we maintain a pre-vetted bench and a structured technical assessment process, not because we send unscreened resumes and call it fast sourcing.

    9Yards Technology has deployed 300+ engineers for enterprise clients including SHL and Talkdesk, maintaining a 95% client retention rate against an industry average of approximately 70%. Talkdesk’s India engineering hub, built in 3 months with 45+ engineers deployed across Engineering, QA, Security, and Business Analysis, is the documented proof point for North America clients evaluating whether offshore India engineering can integrate with a US-headquartered product team.

    Senior AI/ML engineers deployed through 9Yards Technology cost $45,000-$60,000 annually, compared to $180,000-$220,000 for US local equivalents at the same seniority level. That is a verified annual saving of $120,000-$160,000 per senior ML hire, computed from current market benchmarks in Statistics.md. For a 10-person ML team, the annual saving across a typical role mix ranges from $1,050,000 to $1,450,000.

    Do You Have These Queries?

    Frequently Asked Questions

    How quickly can I hire Machine Learning developers through 9Yards Technology?
    Pre-vetted Machine Learning developer profiles are delivered within 48-72 hours of your requirement submission. Full deployment, covering technical assessment, client interview, and onboarding, is completed within 2-3 weeks. The traditional US hiring market averages 90 days for a comparable senior ML role, so 9Yards Technology's process recovers roughly 69 days of lost engineering productivity per hire.
    What Machine Learning technologies do your developers specialise in?
    9Yards Technology deploys Machine Learning developers with verified expertise across TensorFlow, PyTorch, Scikit-learn, Keras, and cloud AI platforms on AWS, Azure, and GCP. Specialists are available across MLOps and pipeline automation, NLP, computer vision, deep learning, predictive analytics, recommendation engines, and generative AI including LLM fine-tuning and retrieval-augmented generation.
    What happens if the ML developer you deploy does not meet our requirements?
    9Yards Technology's written 7-day replacement SLA guarantees that any underperforming Machine Learning developer is replaced within 7 days at no renegotiation cost. This commitment is in the contract before work begins. The SLA is backed by a 95% client retention rate across 300+ engineer deployments, which reflects the quality of the vetting process, not just a contractual fallback.
    How much does it cost to hire offshore Machine Learning developers from India?
    Senior AI/ML engineers deployed through 9Yards Technology cost $45,000-$60,000 annually, compared to $180,000-$220,000 for US local equivalents at the same seniority level. That represents an annual saving of $120,000-$160,000 per senior hire. For a 10-person ML team at senior level, annual savings typically range from $1,050,000 to $1,450,000 depending on role mix.
    Can offshore Machine Learning developers integrate with our US-based engineering team?
    Yes. Talkdesk's India engineering hub, built by 9Yards Technology in 3 months with 45+ engineers deployed across Engineering, QA, Security, and Business Analysis, is the documented proof point. The engagement delivered 80% faster hiring, 50% cost reduction, and enabled seamless collaboration with Talkdesk's US-headquartered product teams. The hub remains active and continues to expand.
    Our Blog

    Dive Into our Insights Horizon

    Go through our informative blogs, providing you with a deep insight into upcoming technologies having the potential for business transformation. Our pieces will equip you in making a sound decision narrowing down the conversion funnel!