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Bridge the Gap Between Data Science and Production With Expert MLOps Engineers

While 87% of machine learning models never reach production, our MLOps engineers ensure your AI initiatives deliver real business value. At EncodeDots, we connect you with senior MLOps professionals who build robust pipelines for continuous training, deployment, and monitoring of machine learning systems. Hire MLOps engineers skilled in Kubeflow, MLflow, and TensorFlow Serving to operationalize everything from computer vision models to LLM-powered applications. Our engineers combine infrastructure expertise with ML domain knowledge to create reproducible, scalable, and observable AI systems.

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    Full-Time Developers

    9 Hours/day

  • part-time-icon
    Part-Time Developers

    4 Hours/day

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    Hourly Hiring

    Pay as you go

MLOps Solutions That Keep Your AI Systems Performing

Production ML systems require 5-10x more code than experimental models to maintain performance at scale. Hire dedicated MLOps engineers who design systems leveraging the latest advancements in feature stores, model registries, and drift detection. Whether you need batch prediction pipelines, real-time inference services, or continuous retraining workflows, we build with reliability and scalability engineered into every component.

  • Model Versioning & Governance
  • Feature Store Implementation
  • CI/CD for Machine Learning
  • Performance Monitoring & Alerting
  • Scalable Inference Serving
  • Cost-Optimized Resource Allocation
Hire our Expert
Winner
18+

Months Avg. Model Lifetime

97%

Model Deployment Success

300+

Production ML Systems

Hire MLOps Engineers for Specialized AI Operationalization

Our experts deliver tailored solutions across industries with framework-specific expertise and infrastructure optimization approaches:

Kubernetes Specialists

Deploy and optimize ML workloads on K8s using Kubeflow, Seldon Core, and Triton Inference Server with autoscaling and GPU utilization monitoring.

    Edge Deployment Engineers

    Implement compressed models for mobile and IoT devices using TensorFlow Lite, ONNX Runtime, and specialized quantization techniques.

      LLM Operations Experts

      Deploy and monitor large language models with vLLM, Text Generation Inference, and custom continuous evaluation frameworks.

        Computer Vision Pipelines

        Build high-throughput image processing systems with NVIDIA Triton, TensorRT, and smart batching for real-time applications.

          Feature Platform Architects

          Design and implement feature stores using Feast, Tecton, or custom solutions for consistent training-serving parity.

            Monitoring Specialists

            Implement comprehensive observability with Prometheus, Grafana, and custom metrics tracking data drift, concept drift, and service health.

              Why AI-First Companies Choose EncodeDots for MLOps

              Machine learning systems fail silently without proper operationalization. Leading organizations hire our MLOps engineers to implement solutions that maintain model accuracy, reduce deployment friction, and provide actionable insights into AI system health. Our implementations consistently achieve 95%+ model uptime, 40-60% lower inference costs, and 3-5x faster iteration cycles compared to manual approaches.

              Trusted by clients, proven results.

              4.8
              (151+ Reviews)

              As a global enterprise, we needed a mobile app that would streamline our operations and provide a seamless experience for our customers. Piyush and his team exceeded our expectations with their ability to understand our complex business processes and develop a customized solution that met all of our requirements.

              Jacob Jones

              Product Designer at Crowny

              I always considered India as a treasure trove of tech savvy startups and EncodeDots and team proved me right. They know how to do more with Angular than any other company I encountered in recent years. My project was kept under the watch round the clock and that’s how they turned the time difference into advantage.

              Patrick

              CEO

              As a startup with a disruptive idea, we knew that our website had to be as unique and innovative as our product. They took our rough concept and turn it into a polished design exceeding our expectations. They were always willing to go the extra mile to align our expectations and choices. Looking back I think, partnering EncodeDots was the turnaround moment for our business.

              Harrison

              CEO

              EncodeDots shaped our little success story in online retail. Their workresonated our unique brand identity and after that there’s no looking back. High five to EncodeDots and their team.

              Lucas

              Founder

              As a global enterprise, we needed a mobile app that would streamline our operations and provide a seamless experience for our customers. Piyush and his team exceeded our expectations with their ability to understand our complex business processes and develop a customized solution that met all of our requirements.

              Daniel

              Co-Founder

              MLOps Architects Who Build AI Factories, Not Just Models

              At EncodeDots, you can hire senior MLOps experts who understand that effective AI requires industrialized workflows, not just algorithms. Our team implements advanced capabilities like canary deployments for models, automated rollback systems, and cost-aware scaling to create ML systems that perform reliably under production loads.

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              • Framework-Specific Specialization
              • Optimized for Performance & Cost
              • Flexible Engagement Models
              • End-to-End ML Lifecycle

              Why Enterprises Trust EncodeDots for Critical MLOps Solutions

              MLOps is the difference between POC purgatory and production impact. Innovative companies hire our dedicated MLOps engineers to implement solutions that bridge the gap between data science and DevOps. Our systems consistently maintain model accuracy within 2% of training performance, reduce deployment times from weeks to hours, and provide complete visibility into AI system behavior.

              From Fortune 500 deployments to AI startups, clients choose us because we understand operationalized ML requires more than containerization - it demands complete lifecycle management. We don't just deploy models; we create learning systems that adapt through automated retraining, performance-aware scaling, and continuous data quality monitoring.

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              MLOps Success Stories at EncodeDots

              From financial forecasting to medical diagnostics, our MLOps implementations power reliable AI across industries. Here's an in-depth look at one of our transformative projects:

              Hire our Expert

              Real-Time Fraud Detection System

              We productionized an ensemble ML system for a payment processor handling 5,000 TPS with <50ms latency requirements and strict model governance needs.

              • UI/UX Design
              • Mobile App Development
              • 99.98% Inference Uptime
              • 45% Reduction in Cloud Costs
              • 3x Faster Model Iteration
              • Full Audit Trail Compliance
              • 4.9/5 Operational Satisfaction

              Tech Stack Deployed

              Explore Case Study

              Hire MLOps Engineers for Industry-Specific AI Operationalization

              Enterprises partner with our MLOps specialists to build tailored deployment pipelines across these critical sectors:

              Financial Services AI

              • Fraud Detection Ops Engineer
              • Risk Model Deployment Specialist
              • Real-Time Inference Architect
              • Model Governance Compliance Expert
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              Healthcare & Life Sciences

              • Medical Imaging Pipeline Engineer
              • HIPAA-Compliant Deployment Specialist
              • Patient Risk Monitoring Architect
              • Clinical Trial Analytics Ops Expert
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              Retail & E-Commerce

              • Recommendation System Engineer
              • Dynamic Pricing Deployment Specialist
              • Inventory Forecasting Ops Architect
              • Customer Churn Monitoring Expert
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              Autonomous Systems

              • Sensor Fusion Deployment Engineer
              • Real-Time Perception Ops Specialist
              • Edge Model Optimization Architect
              • Vehicle Control System Expert
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              Industrial IoT

              • Predictive Maintenance Engineer
              • Anomaly Detection Ops Specialist
              • Equipment Monitoring Architect
              • Quality Control Deployment Expert
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              Media & Advertising

              • Content Moderation Ops Engineer
              • Ad Targeting Deployment Specialist
              • Personalization System Architect
              • Viewer Analytics Pipeline Expert
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              Flexible Hiring Options
              • Full-Time MLOps Pros

                9 Hours/day

              • Part-Time MLOps Experts

                4 Hours/day

              • Hourly MLOps Experts

                Pay as you go

              Work With Our MLOps Team

              • Production-Grade Reliability
              • Cost-Optimized Scaling
              • Continuous Model Improvement
              Launch MLOps Now!

              Hire MLOps Engineers in 4 Streamlined Steps

              At EncodeDots, we've perfected the process of connecting you with elite MLOps talent:

              • 01

                Define Your ML Infrastructure Needs

                Share your model frameworks, scale requirements, and latency targets. We match specialists based on your tech stack and deployment environment.

              • 02

                Receive Curated Engineer Profiles

                Within 48 hours, get 3-5 pre-vetted MLOps engineers with portfolios demonstrating production deployments and performance benchmarks.

              • 03

                Conduct Technical Evaluations

                Assess candidates through MLOps challenges, including pipeline creation, scaling exercises, and monitoring implementations.

              • Begin Deployment in 72 Hours

                Selected engineers onboard with full environment access and start productionizing models within three business days.

              Why AI Leaders Choose EncodeDots for MLOps

              Production ML systems demand specialized expertise across the deployment pipeline, and our engineers deliver measurable results through technical excellence.

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              Framework Mastery

              Deep expertise in TensorFlow Serving, TorchServe, Triton, and custom model deployment architectures.

              Scale Optimization

              Systems designed for 100-100,000+ RPS with intelligent batching, model partitioning, and hardware-aware scheduling.

              Lifecycle Automation

              CI/CD pipelines for ML incorporating testing, canary deployments, and automated rollback capabilities.

              Enterprise Reliability

              99.5%+ uptime implementations with multi-region failover and performance degradation safeguards.

              Cost Governance

              Resource allocation strategies that typically reduce inference costs by 40-60% without sacrificing latency.

              Technology Stack

              Our MLOps engineers work with Kubeflow, MLflow, and Airflow for orchestration; Seldon Core and Triton for inference; Feast and Tecton for feature stores; Prometheus and Grafana for monitoring. We deploy on AWS SageMaker, GCP Vertex AI, and Azure ML while maintaining vendor-agnostic portability.

              Programming languages

              Environments and Frameworks

              • XCode
              • Xamarin
              • Ionic
              • Eclips
              • Cordova
              • NetBeans
              • iOS SDK

              Backend Programming

              Databases

              • SQLite
              • Realm
              • Firebase
              • AWS
              • Microsoft Azure

              QA tools

              • TestFlight
              • XCTest
              • Detox
              • EarlGrey
              • Appium
              • JUnit
              • .NET Foundation

              DevOps

              • Docker
              • Kubernetes
              • Ansible
              • Terraform
              • Jenkins
              • Azure Devops
              • Packer
              • Saltstack
              • CI CD
              • Teamcity

              APIs

              • Apple Pay
              • Google Maps
              • Google Pay
              • Apple Maps
              • Rest-API
              • GraphQL

              EncodeDots Simplifies Hiring Production MLOps Experts

              48-Hour Talent Matching

              Get MLOps engineer profiles aligned with your framework and scale requirements within two business days.

              Top 3% ML Engineers

              Rigorous screening evaluating pipeline design skills, performance optimization, and incident response.

              60% Faster to Production

              Pre-built deployment templates and modular architecture patterns accelerate time-to-value.

              Transparent Pricing

              Clear rates based on specialization ($90-200/hr) with detailed cost breakdowns.

              Global Compliance

              Full HR management covering contracts, IP protection, and data regulations across 30+ countries.

              Real-Time Collaboration

              Engineers available during your business hours with 6+ hours of timezone overlap.

              Production-Ready in 72h

              MLOps specialists onboarded with full environment access within three days.

              Flexible Scaling

              Adjust team size from initial deployment to ongoing optimization as needs evolve.

              97% Retention

              Engineers average 20+ months of engagements, ensuring system continuity.

              Partner with Our MLOps Engineers for AI That Works

              Whether deploying first models or scaling to enterprise workloads, our certified professionals deliver production-grade ML systems. We combine platform expertise with domain knowledge to operationalize AI that delivers consistent business value while maintaining performance, reliability, and cost efficiency.

              Hire Developer
              Table of contents
              • Businesses Idea
              • Hire MLOps Engineers
              • EncodeDots for MLOps
              • Critical MLOps Solutions
              • MLOps Success Stories
              • Hire MLOps Teams
              • MLOps Hiring Steps
              • Why Choose EncodeDots
              • Technology Stack
              • Simplifies Hiring Production

              Frequently Asked Questions

              Need Expert MLOps Engineers? Let's Talk!

              • Production-Grade Deployments
              • Continuous Model Improvement
              • Enterprise Scaling Expertise
              Consult On Your ML Deployment Today!

              Our streamlined MLOps process delivers production-ready deployments in 2–4 weeks. We containerize models within 3–5 days, establish CI/CD pipelines by week 2, and implement monitoring by week 3, with remaining time for load testing and optimization. Complex distributed systems may require additional iterations.

              Our MLOps specialists range from $90-220/hour based on system complexity. Basic model serving implementations start at $90-130/hour, Kubernetes-based deployments average $130-170/hour, and large-scale distributed systems reach $170-220/hour. These investments typically pay for themselves through 40-70% lower cloud costs and reduced model downtime.

              Yes, we provide complete MLOps teams including Pipeline Engineers, Feature Platform Specialists, Monitoring Experts, and Cloud Architects. Teams scale from 2-person pods for specific deployments to 15+ member units for enterprise AI factories, all managed through unified governance.

              Our experts have production experience with TensorFlow, PyTorch, Scikit-learn, XGBoost, and custom frameworks. We implement framework-optimized serving patterns and can advise on technology selection based on your performance requirements.

              We implement comprehensive monitoring for data drift, concept drift, and service metrics with automated alerting. Typical solutions include scheduled retraining pipelines, canary deployments, and fallback strategies that maintain 99%+ prediction quality.

              We've successfully improved 100+ production ML systems through our assessment framework, evaluating serving architecture, resource allocation, and monitoring coverage. Typical improvements include 50-80% cost reduction and 2-5x throughput increases.

              All architectures implement model encryption, access controls, and audit trails. We meet HIPAA, GDPR, and SOC 2 requirements where applicable through secure deployment patterns and data governance.

              We design resilient architectures using multi-region setups, health checks, failovers, and load balancing to ensure 99.9%+ uptime—even during outages or high-traffic events.

              Our engineers regularly connect ML systems with Snowflake, Databricks, Kafka, and on-premise data warehouses, implementing proper authentication and throughput management.

              We deliver complete system diagrams, runbooks, and infrastructure-as-code documentation, with optional training sessions for your team on maintenance and troubleshooting.

              Explore More AI Engineering Expertise at EncodeDots

              We provide specialized engineers across the machine learning lifecycle to build comprehensive AI solutions tailored to your technical requirements.

              Hire Machine Learning Engineers

              Develop sophisticated ML models with our algorithm specialists who combine advanced techniques with domain expertise to solve complex business problems.

              Hire AI Engineers

              Create intelligent AI systems with our deep learning engineers who apply neural network innovations and domain insight to overcome business challenges.

              Hire LLM Engineers

              Implement large language model solutions with our NLP specialists skilled in fine-tuning, RAG architectures, and domain-specific optimization.

              Hire Computer Vision Engineers

              Develop image and video analysis systems with our CV experts who build solutions for object detection, facial recognition, and visual search.

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              Project Inquiries

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              India

              517, City Center 2, Science City Rd, Ahmedabad 380060

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