Data Engineer for AI Voice Infrastructure

@AwaisChaudhry

Hello, I understand that Novaia is seeking a skilled Data Engineer with MLOps expertise to enhance your AI voice infrastructure. My approach will involve developing and maintaining efficient data pipelines for audio and text processing, ensuring robust model deployment through a complete MLOps workflow, and optimizing inference times for your NLP, STT, and TTS models on GPUs. I have extensive experience with Docker, Kubernetes, and various ML frameworks, which will aid in industrializing workflows and automating model tracking and performance monitoring effectively. What specific challenges have you encountered with your current AI voice infrastructure that you would like me to address? Thanks, Muhammad Awais

@dahani9091

Scaling AI voice infrastructure can be challenging, especially when it comes to deploying performant models efficiently. Most companies struggle with optimizing data pipelines and ensuring smooth MLOps workflows, which can lead to latency issues and operational bottlenecks. To address your needs, I propose the following approach: 1. Assess existing data pipelines and identify optimization opportunities for ETL processes. 2. Implement a robust MLOps workflow that includes CI/CD for seamless deployment and monitoring. 3. Optimize NLP/STT/TTS model inference on GPUs, targeting latency under 300 ms. 4. Industrialize and automate workflows using Docker and Kubernetes, ensuring scalability. 5. Set up model tracking and performance monitoring with tools like MLflow or Weights & Biases. I recently helped a client in the AI voice domain streamline their MLOps processes, leading to a 40% reduction in deployment time and significant improvements in inference speed. As a starting point, focusing on your audio/text preprocessing can yield immediate benefits. I recommend evaluating the current preprocessing methods for efficiency. I’d love to discuss how we can tailor a solution for Novaia’s specific challenges. Please feel free to reach out.

@ZohaibRoy

⭐⭐⭐⭐⭐ Data Engineer with MLOps Skills for AI Voice Infrastructure ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and see you're looking for a Data Engineer with MLOps skills. You don't need to look any further; Zohaib is here to help! My team has successfully completed 50+ similar projects for AI infrastructure. I will build and maintain robust data pipelines, implement efficient MLOps workflows, and optimize model inference to meet your scalability needs. ➡️ Why Me? I can easily handle your data engineering and MLOps needs as I have 5 years of experience in building data pipelines, deploying models, and optimizing workflows. My expertise includes Python, SQL, Docker, and Kubernetes, ensuring a solid foundation for your project. I also have a strong grip on ML frameworks like PyTorch and TensorFlow, allowing me to efficiently manage your AI models. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. I look forward to discussing this with you! ➡️ Skills & Experience: ✅ Data Engineering ✅ MLOps ✅ Python ✅ SQL ✅ Docker ✅ Kubernetes ✅ GitLab CI/CD ✅ ML Frameworks ✅ PyTorch ✅ TensorFlow ✅ GPU Optimization ✅ Model Monitoring Waiting for your response! Best Regards, Zohaib

@LiveExperts

Hello, As a seasoned Data Engineer with extensive knowledge in AI and strong MLOps capabilities, I believe I am the right fit for your project. My team at Live Experts® LLC has a wealth of experience in all aspects of your requirement, including ETL, Docker and Kubernetes management, PyTorch and TensorFlow, GPU optimization, and MLOps. These skills are the ingredients needed for optimizing and deploying your models in a scalable manner. Throughout my career, I have not only built robust data pipelines but also overseen the complete MLOps workflow, from training to CI/CD to monitoring and deployment. I understand the importance of maintaining performance while scaling up an infrastructure, especially one as critical as yours. Hence, I aim to bring in the operational efficiency you require through industrializing workflows and managing containerized environments. Lastly, my proficiency in French NLP would be an added value for your project. Having worked on real-time systems and audio streaming before, I’m confident in my ability to deliver quality work within your project's latency requirements. Let's discuss further on how we can implement your AI voice infrastructure at Novaia using the exacting standards that you need. We’re ready to dive into this exciting chapter with you! Thanks!

@intelliresponse

With over 13 years of experience as a specialized Data Engineer and AI Solution developer, I am the right freelancer for your Novaia project. My skills and expertise align well with your project's needs. I have a strong background in MLOps and Data Engineering, which is crucial for building and maintaining the robust data pipelines you require for ETL, audio/text preprocessing, and implementing an end-to-end MLOps workflow. I also bring extensive experience in real-time systems including audio streaming that will be invaluable in deploying your models efficiently. Finally, my exposure to NLP technologies further enhances my value add taking into account your requirement for dealing with large scale speech-to-text & text-to-speech processes. Overall, my comprehensive skill-set ensures I can effectively industrialize workflows from data scientists ito managed containerized environments (Docker, Kubernetes), automate tracking with tools like MLflow & Weights & Biases while tirelessly monitoring performance - allowing you to scale your AI voice infrastructure successfully. Let's get started on optimizing and scaling your infrastructure together!

@mannanmaan1425

Hello Raymond M., I have read the project details and understood the overall requirement. I am Abdul, a seasoned Data Engineer with expertise in Python, Hadoop, Spark, Kubernetes, ETL, GCP AI, NLP, Model Deployment, and MLOps. With 5 years of experience, I have successfully delivered multiple projects in similar domains. For the AI Voice Infrastructure project, I plan to build robust data pipelines for ETL and preprocessing, implement a comprehensive MLOps workflow, optimize GPU inference for NLP/STT/TTS models, industrialize workflows, and automate model tracking and monitoring. You can view my portfolio here: https://www.freelancer.com/u/mannanmaan1425 Please ping me back so we can discuss the project further in the chat. Best regards, Abdul

@irsolutions

With over a decade of experience in web and mobile development, specializing in AI/ML solutions, I understand the importance of scaling and productionizing your AI voice infrastructure. Your project at Novaia aligns perfectly with my expertise in MLOps and data engineering. I have successfully built and optimized data pipelines, implemented MLOps workflows, and managed containerized environments for clients in various industries, including healthcare and FinTech. My experience with Python, Docker, Kubernetes, and ML frameworks like PyTorch and TensorFlow make me well-equipped to tackle the challenges of your project. I am particularly excited about the opportunity to optimize inference on GPUs and automate model tracking for your AI voice platform. My track record of deploying efficient and scalable solutions will ensure the success of your project at Novaia. Let's discuss further how I can contribute to your project as a freelance Data Engineer. Looking forward to hearing from you soon.

@OmarFarukBD

I AM NOT LIKE OTHER 99% OF SELLERS. YOU WILL PAY ONLY AFTER THE WORK IS COMPLETE, AND I ONLY FOCUS ON EXPLAINING WHAT I UNDERSTAND. PLEASE READ IT. I am going to start your project right now. I will build and optimize robust data pipelines, implement full MLOps workflows, and deploy your AI voice models efficiently on GPU clusters. Using Python, Docker, Kubernetes, and ML frameworks like PyTorch and HuggingFace, I will ensure real-time inference under 300ms with full monitoring, automation, and scalability.

@divumanocha

Hello, I came across your project and found it truly interesting. With over eight years of hands-on experience in this field, I have successfully delivered high-quality solutions to clients worldwide. My dedication to excellence is reflected in the 180+ positive reviews from satisfied clients. I’d love to bring this expertise to your project and ensure outstanding results. However, I do have a few important points I’d like to clarify to align perfectly with your vision. Let’s connect via chat, where I can also share relevant examples of my past work. I'm looking forward to hearing back from you! Best Regards, Divu.

@letsUnlockAI

Hi, I’d love to support Novaia in scaling your AI voice infrastructure. I bring 6+ years in Data Science and MLOps, with hands-on experience in Python, SQL, Docker, Kubernetes, and CI/CD pipelines. I’ve built GPU-optimized STT/TTS pipelines (PyTorch, HuggingFace) with sub-300 ms inference. I can design robust ETL pipelines for audio/text and integrate monitoring via MLflow or W&B. My focus is on productionizing research workflows into reliable, scalable deployments.

@denisSolution

Hello client, I'm Denis Redzepovic, an experienced developer with expertise in MLOps, Kubernetes, GCP AI, Data Engineer, Python, Model Deployment, Spark, Hadoop, NLP and ETL. I have worked extensively on diverse Python projects, ranging from backend development and automation to data processing and API integrations. My deep understanding of Python’s libraries and frameworks allows me to build efficient, scalable, and maintainable solutions. I pay close attention to code quality and performance to ensure your project runs flawlessly. With my solid experience, I’m confident I can deliver results that exceed your expectations. I focus on writing clean, maintainable, and scalable code because I know the difference between 99% and 100%. If you hire me, I’ll do my best until you’re completely satisfied with the result. Let’s discuss your project details so I can tailor the perfect Python solution for you. Thanks, Denis

@Rekhathakur

Hello, As a seasoned and experienced data engineer with a strong background in MLOps, I am confident in my ability to optimize and scale Novaia's AI voice infrastructure. My team at WellSpring Infotech specializes in custom development and has worked extensively with Python, SQL, Docker, Kubernetes and GitLab/GitHub CI/CD - exactly the skills you're seeking. One of our core competencies is building robust data pipelines for ETL processes, which will be crucial for efficient management and automation of your organisation's modelling workflows, as you mentioned in your project requirements. Lastly, my team's commitment to comprehensive project management ensures that we will not only successfully build and optimize your AI voice infrastructure but also provide diligent, consistent monitoring to ensure it remains up-to-date. By selecting us for this role, you'll be partnering with a dedicated team that values your business goals and is committed to driving innovation through technology. Let's discuss how we can transform your operational efficiency with a powerful AI voice infrastructure! Thank you

@Feriver

Hello, I understand you’re looking for a Data Engineer with strong MLOps expertise to productionize and scale your AI voice infrastructure. With extensive experience in real-time AI platforms, I can design and optimize data pipelines, implement end-to-end MLOps workflows, and ensure your speech-to-text, text-to-speech, and NLP models run efficiently in multi-server GPU environments. My focus is achieving sub-300 ms latency through GPU optimization and scalable container orchestration. I have successfully built ETL pipelines for audio and text data, containerized ML workflows with Docker and Kubernetes, and automated deployment and monitoring using GitLab CI/CD, MLflow, and Weights & Biases. Leveraging frameworks like PyTorch and HuggingFace, I can integrate your existing models into a robust production environment with continuous monitoring and retraining. My approach emphasizes fault-tolerance, reproducibility, and seamless scaling across GPU clusters. The deliverables will include a production-ready MLOps workflow, optimized GPU inference pipelines, automated monitoring dashboards, and CI/CD integration. The result will be a resilient, high-performance infrastructure supporting real-time AI voice services at scale. Thanks, Asif

@gm341473

With my substantial expertise in Python, MLOps, and Data Engineering, I am perfectly suited for the challenges that your project entails. Having undertaken similar projects in the past, I understand the importance of building and maintaining efficient data pipelines as well as implementing an effective MLOps workflow that encompasses every aspect from training to monitoring. Moreover, my knowledge of GPU optimization (including NVIDIA L4, A100, H100) adds another dimension to my candidacy. Another distinguishing aspect of my profile is my deep understanding of major ML frameworks like PyTorch, HuggingFace, and TensorFlow. This expertise will be instrumental in optimizing the inference capabilities of your NLP/STT/TTS models on GPUs with target latency under 300 ms. Furthermore, managing containerized environments using Docker and Kubernetes is second nature to me, making me an asset when it comes to industrializing working flows from data scientists. Lastly, I make it a point to automate model tracking and performance monitoring using tools like MLflow and Weights & Biases for an enhanced experience. This ensures that all aspects are monitored diligently with minimal human intervention thereby reducing the chances of error. For a comprehensive approach combined with extensive skills,

@martin926

Hello, I have strong experience in MLOps, Data Engineering, and scaling AI models into production. I can help you optimize and deploy your real-time AI voice infrastructure with GPU-based inference under strict latency requirements. I have previously worked on real-time AI and audio systems, ensuring low latency and high reliability in multi-server clusters. Let’s discuss your infrastructure goals—I’m confident I can help you scale efficiently. Best regards,

@datacode0023

Hello, I have +7 years of experience dealing with AI Projects and worked on multiple projects in this field, I have extensive experience with: docker CI/CD elastic/kibana apache mlflow and airflow. (I can send over my work samples.) PyTorch, HuggingFace, TensorFlow please start a chat with me so I can send over my work samples. Have a nice day

@Ekarthaan

Hi Raymond M., I recently completed a very similar project. I can show u sample. - Questions: 1) What are your end-to-end SLOs by percentile (p50/p95/p99) and per-stage budgets for STT→NLP→TTS, including target chunk size/stride, partial hypothesis cadence, and transport (gRPC bi-di, WebRTC, or RTP) jitter constraints? 2) What’s the expected peak concurrent calls and GPU mix (L4/A100/H100)? Do you have per-model memory footprints and desired per-GPU concurrency to size dynamic batching, beam params, and precision (FP16/INT8/FP8)? Are you standardizing on Triton/KServe today? - Suggestions: 1) Production serving: Use Triton with model ensembles (VAD→STT→NLP→TTS), enable TensorRT, CUDA Graphs, mixed precision, and INT8/FP8 where accuracy holds; configure dynamic batching with tight max_queue_delay for <300 ms; isolate via MIG on A100/H100; leverage DCGM for autoscaling signals; gRPC bi-di with jitter buffer/backpressure; vLLM for NLP with paged attention and KV-cache pinning Kindly send me a message, lets discuss in detail and my portfolio is uploaded here and on my website. Best Regards, Sid CTO and Co-Founder of Ekarthaan

@abhisaini0188

Hello, Thank you so much for posting this opportunity it sounds like a great fit, and I’d love to be part of it! I’ve worked on similar projects before, and I’m confident I can bring real value to your project. I’m passionate about what I do and always aim to deliver work that’s not only high-quality but also makes things easier and smoother for my clients. Feel free to take a quick look at my profile to see some of the work I’ve done in the past. If it feels like a good match, I’d be happy to chat further about your project and how I can help bring it to life. I’m available to get started right away and will give this project my full attention from day one. Let’s connect and see how we can make this a success together! Looking forward to hearing from you soon. With Regards! Abhishek Saini

@efanntyo

Hello Raymond M. Hope you are doing well! This is Efan , I checked your project detail carefully. I am pretty much experienced with GCP AI, NLP, Model Deployment, Python, Hadoop, Kubernetes, Data Engineer, MLOps, Spark and ETL for over 8 years, I can update you shortly. Cheers Efan

@maddifreelancer

Hi, as a proficient python data scientist , i can complete this deployment task perfectly and quickly.I can start working on the project immediately.I can assure you that the best solution will be provided for you. Please contact me to discuss further.