AI/ML Engineer-South-East Asia

@gunslinger

Hi, I’m an AI/ML engineer with over 3 years of hands on experience building and deploying production-grade ML systems. I’ve worked on end to end pipelines, from data preprocessing and model training using PyTorch and scikit learn to deployment on AWS with Docker and CI/CD workflows. I’m comfortable designing scalable ML pipelines, handling model monitoring and retraining strategies, and collaborating closely with data engineers to ensure reliable data flow. I also have experience exploring LLM based solutions and building practical AI features that move from prototype to production. Would be happy to discuss how I can contribute to your ML roadmap. Best, Yuda

@LiveExperts

Hello, As an AI/ML Engineer based in South-East Asia and residing in the Philippines, I am uniquely equipped to tackle the challenges of your project. Over the last 3+ years, I have built and deployed ML models for various real-world applications including NLP and computer vision, which resonates deeply with what you're looking for. Proficiency in Python and a number of ML frameworks is the foundation of my work, along with extensive experience on cloud platforms like Azure and GCP, aligning with your need for infrastructure-as-code. In addition to strongly emphasizing data flow cleanliness and reliability as per your requirements, I take a granular approach toward model performance monitoring, drift detection, retraining strategies, and ethical AI, three essential aspects of the work that often get overlooked. My experiences working with tools like Docker, Kubernetes, and implementing CI/CD for ML workflows fuel efficiency in executing projects such as these. I would also like to highlight the value I bring as a mentor. At Live Experts LLC, we believe in holistic development, which is why we encourage our engineers to not just solve specific technical problems but also share their knowledge effectively. It's this belief that makes me confident about my ability to contribute to both your technical strategy and architecture decisions while nourishing a collaborative environment. Navigating the complexities of ML operations (MLOps), mo Thanks!

@devendrathakur12

Hello, I specialize in production ML systems and built & customized large scale AI pipelines. The main challenge here is deploying models that stay accurate in real-world use and scale without breaking. I am certified in Python development and I will solve this using PyTorch, MLflow, Airflow, Docker, and AWS-based MLOps pipelines. What is your current cloud stack? Do you already track model drift? Batch or real-time inference? Any LLM or RAG plans soon? I focus on stable, monitored production AI. Best regards, Devendra S.

@hireageek

Hi there, I’m excited about the opportunity to work on this AI/ML Engineer project! With over 3 years of hands-on experience in building and deploying machine learning models, particularly in NLP and computer vision, I am confident in my ability to deliver high-quality solutions. I have a strong background in Python and frameworks such as PyTorch and TensorFlow, complemented by experience with cloud platforms like AWS and Azure. My expertise in optimizing ML pipelines using tools like Kubeflow and MLflow ensures that I can create scalable solutions tailored to your needs. Additionally, I have a solid understanding of ethical AI practices and model governance, as well as the ability to effectively communicate complex concepts to both technical and non-technical stakeholders. I would love to discuss how I can contribute to this project and help mentor junior engineers along the way. Please feel free to reach out to me directly! What specific machine learning challenges or projects do you foresee arising in this role? Thanks,

@jinufeb14

With over three years of hands-on experience designing and deploying machine learning models in production, I am the AI/ML engineer you're looking for. I bring out-of-the-box thinking and a meticulous approach to building and optimizing scalable ML pipelines using tools like Airflow, Kubeflow, MLflow, and SageMaker. Additionally, my solid understanding of data structures, algorithms, and software engineering best practices ensures that your project will be equipped with the latest tech solutions. Meanwhile, my familiarity with cloud platforms such as AWS, GCP, and Azure combined with my experience in infrastructure-as-code using Terraform and CloudFormation make me adept at integrating your projects into these environments seamlessly. Moreover, my expertise in containerization (Docker, Kubernetes) and CI/CD for ML workflows enables me to streamline your project processes efficiently. Lastly, beyond just my tech skills, I pride myself on excellent communication that allows me to effectively collaborate with cross-functional teams and explain complex technical concepts even to non-technical stakeholders. As part of this collaboration I always ensure data quality by working closely with data engineers guaranteeing clean,reliable data flows from source to model. In conclusion , I provide end-to-end solution expertise from the initial prototype to building a production-ready model. Let's turn ideas into reality!

@corpmember29

HELLO, I’m very interested in the AI/ML Engineer role and align strongly with your production-focused requirements. I have 5+ years of hands-on experience deploying ML systems, I’ve built and maintained models across NLP, forecasting, and recommendation domains — moving from research prototypes to scalable production services. Core Strengths • Python expert (PyTorch, TensorFlow, scikit-learn, Hugging Face) • End-to-end ML pipelines (training → validation → deployment → monitoring) • MLOps experience with Docker, Kubernetes, CI/CD workflows • Cloud-native deployments (AWS / GCP) • Model tracking & lifecycle management (MLflow) • Drift detection & retraining strategies Advanced Experience • LLM integration & RAG pipelines • Generative AI feature prototyping • Data pipeline collaboration (Spark, Kafka, warehouse integration) • Production monitoring & governance best practices I’m comfortable collaborating cross-functionally, mentoring junior engineers, and contributing to architecture decisions — especially in fast-moving, product-focused environments. I’m currently based in South-East Asia and available for long-term engagement. Looking forward to discussing how I can contribute to your ML initiatives.

@tangramua

Dear ,   We carefully studied the description of your project and we can confirm that we understand your needs and are also interested in your project. Our team has the necessary resources to start your project as soon as possible and complete it in a very short time.   We are 25 years in this business and our technical specialists have strong experience in Python, Azure, CUDA, Machine Learning (ML), Data Mining, Docker, Kubernetes, Terraform, Hugging Face, MLOps and other technologies relevant to your project.   Please, review our profile https://www.freelancer.com/u/tangramua where you can find detailed information about our company, our portfolio, and the client's recent reviews.   Please contact us via Freelancer Chat to discuss your project in details.    Best regards, Sales department Tangram Canada Inc.     

@juanjosec63

Hello, I’m excited about the opportunity to contribute to your team. With hands-on experience designing and deploying production-grade ML systems in Python using PyTorch, scikit-learn, and Hugging Face, along with building scalable pipelines on AWS and Azure using Docker, Kubernetes, and Terraform, I can help deliver robust models supported by solid MLOps practices, monitoring, and automated retraining workflows. I’ve worked across end-to-end ML lifecycles—from data ingestion and feature engineering through training, evaluation, deployment, drift detection, and governance—while collaborating closely with data engineers to ensure reliable pipelines and translating research ideas (including LLM and RAG-based prototypes) into stable production features. You can expect strong technical ownership, clear communication with both engineering and non-technical stakeholders, and a proactive approach to architecture decisions, mentorship, and long-term model reliability. Best regards, Juan

@OutsourceMan

⭐⭐⭐⭐⭐ We at CnELIndia, led by Raman Ladhani, can help execute this project end-to-end by leveraging our expertise in designing, training, and deploying production-grade ML models across NLP, computer vision, and recommendation systems. We can build and optimize scalable pipelines using Airflow, Kubeflow, MLflow, or SageMaker, ensuring clean data flows in collaboration with data engineers. Our team implements robust monitoring, drift detection, and retraining strategies while prototyping AI capabilities into production-ready features. With deep proficiency in Python, PyTorch, TensorFlow, Hugging Face, cloud platforms (AWS, Azure, GCP), containerization, and CI/CD, we ensure best practices in MLOps, governance, and ethical AI. We also mentor engineers, translate research into practical solutions, and accelerate model adoption using feature stores and advanced monitoring tools, ensuring reliable, scalable, and innovative ML delivery.

@avinashdubeyg209

Hi there, I am an ML engineer. I can start right away and deliver within the deadline. So, Let’s have a quick conversation. I can be more specific once we get all the requirements and information required to execute the project. Thank you!!

@usmanbashir12100

Hi, I’m an experienced Machine Learning Engineer with 3+ years of production ML experience, building and deploying models across NLP, computer vision, and forecasting use cases. I’ve designed scalable ML pipelines using tools like Airflow/MLflow, deployed models on AWS/GCP, and implemented monitoring, drift detection, and retraining workflows. I work closely with data engineers to ensure reliable data flows, follow strong MLOps and governance practices, and translate research into production-ready systems. I’m comfortable mentoring juniors and contributing to architecture and technical strategy. My stack includes Python, PyTorch, TensorFlow, scikit-learn, Docker/Kubernetes, CI/CD, and IaC. I also have exposure to LLMs, RAG pipelines, and generative AI, and I enjoy building products from 0→1 in fast-moving environments.

@Julian29

I have reviewed your requirements and understood the scope of designing, training, and deploying production-ready ML models across NLP, computer vision, forecasting, and recommendation systems. I have 10+ years of experience in Python, PyTorch, TensorFlow, scikit-learn, and building scalable ML pipelines with Airflow, Kubeflow, MLflow, and cloud platforms (AWS/GCP/Azure). I will provide 2 years free ongoing support and complete source code, work with Agile methodology, and assist from zero to production deployment. My approach includes clean, reliable data pipelines, containerized CI/CD workflows, model monitoring and drift detection, retraining strategies, and AI feature prototyping. I am also experienced mentoring teams and implementing MLOps best practices, ethical AI guidelines, and governance frameworks. I am available in your time zone for long-term collaboration and will ensure solutions are production-grade, scalable, and maintainable. I eagerly await your positive response. Thanks

@Ahmedh058

Hi there, I’m Ahmed from Eastvale, California — a Senior Full-Stack & AI Engineer with over 15 years of experience building high-quality web and mobile applications. After reviewing your job posting, I’m confident that my background and skill set make me an excellent fit for your project — AI/ML Engineer-South-East Asia . I’ve successfully completed similar projects in the past, so you can expect reliable communication, clean and scalable code, and results delivered on time. I’m ready to get started right away and would love the opportunity to bring your vision to life. Looking forward to working with you. Best regards, Ahmed Hassan

@softsolution2000

I bring 15 years of experience to the AI/ML Engineer-South-East Asia project, with expertise in Python, Azure, CUDA, Machine Learning (ML), and Data Mining. I am confident that my skills align perfectly with your requirements. I am open to adjusting the budget based on project scope and eager to discuss further details. My priority is delivering quality work within your budget. Please review my profile for past work, as client satisfaction is my top priority. I am ready to start working and showcase my commitment to this project. Looking forward to hearing from you.

@xuezhe315

Hello, With over 3 years of hands-on experience in building and deploying ML models in production, I am well-versed in the design, training, and deployment of AI/ML models for real-world applications, something that aligns perfectly with your project description. My expertise extends into various ML frameworks including TensorFlow, PyTorch, scikit-learn, as well as cloud platforms such as Azure - all skills required for this position. Additionally, I am just where you need me to be — residing in South East Asia (Philippines) so there are no logistical challenges to tackle. Throughout my career as a seasoned software engineer, I have developed a keen understanding of data structures, algorithms and software engineering best practices. This coupled with my fluency in Python and proficiency in tools like Airflow and SageMaker makes me perfectly suited for building and optimizing scalable ML pipelines. I pride myself on championing best practices in MLOps and model governance - crucial aspects highlighted in your project. I am confident that I could add value not just by delivering on the technical requirements but also by driving measurable business growth with strategic inputs at every stage. Regards.

@hotanloc

Hi. Client. Thanks for your posting. I am an expert AI programer with more than 5 years. I have expertise in ML/DL, and neural network, SVM, decision tree, and other all models.I I have full experiences in TensorFlow, PyTorch, Scikit-learn and other libraries. I have completed many projects such as neural style transfer, object detection, data prediceion and forecasting... I checked your proposal carefully. I can finish your task perfectly on time. Please send me your message to discuss your project detail more...I am waiting your reply now. Thanks.

@mayankinnovative

Hi, As per my understanding: You are hiring a production-focused ML Engineer (Philippines / SEA based) who can design, deploy, and scale real-world ML systems. The role goes beyond modeling into full MLOps ownership: pipeline orchestration, cloud deployment, monitoring, drift detection, retraining strategy, and governance. You need someone comfortable with Python, PyTorch/TensorFlow, containers, CI/CD, and cloud infra, ideally with LLM/RAG exposure and 0→1 product mindset. Implementation approach: I would approach this role with a production-first ML architecture mindset. Models will be designed with reproducibility and scalability in mind, tracked via MLflow, orchestrated with Airflow/Kubeflow, and deployed through containerized services on AWS/GCP using Terraform-based infrastructure. I ensure clean feature pipelines in collaboration with data engineering, implement monitoring (drift, data quality, performance), and automate retraining workflows. For LLM or RAG use cases, I would design modular embedding + retrieval pipelines with evaluation benchmarks before rollout. Documentation, governance standards, and mentoring will be integrated into delivery. A few quick questions: • What is your current ML stack and cloud provider? • Are you starting new initiatives or optimizing existing models? • Do you already have CI/CD for ML in place? • What level of LLM integration is expected initially?

@JijoThomas2020

Hi, I’m an ML Engineer with 3 plus years of hands on experience designing, training, and deploying production models across NLP and document understanding, and I can help you ship reliable ML features with strong MLOps. In recent work, I built end to end ML pipelines in Python using PyTorch, scikit learn, and Hugging Face, then productionized them with Docker, Kubernetes, CI CD, and cloud services on AWS. I’m comfortable setting up Airflow or MLflow style workflows, adding monitoring and drift checks, and building retraining loops that are simple to operate. I also work closely with data engineers to make sure the data is clean and reproducible from source to model. I can contribute to architecture decisions, mentor junior engineers, and communicate clearly with non technical stakeholders so projects keep moving. If you share your current stack and the first model you want to ship, I can propose a clear first milestone plan and start immediately.

@Rekhathakur

Hello, With over a decade of experience in software development, my team at WellSpring Infotech is well-equipped to handle this demanding AI/ML project. Our expertise lies in building and deploying machine learning models in production- a skillset that directly aligns with your needs. We are well-versed in several ML frameworks like PyTorch, TensorFlow, and scikit-learn as well as experienced in managing cloud platforms effectively like AWS, GCP, and Azure. Our forte also extends into advocating for MLOps, model governance, and ethical AI - an aspect crucial for any forward-thinking organization. Apart from the technical aspects, we hold great importance to communication skills and understanding stakeholders' diverse needs- making sure we're always on the same page. Drawing from our startup experience, we not only build but also nurture products to life including those that rely heavily on AI/ML like the one you envision. Another competency we bring to the table is our ability to mentor junior engineers - an important requirement mentioned in the project description. This implies a deep understanding of not just the technology but also successful methods of transferring it to others- something we've honed over years. Furthermore, having dealt with data engineering solutions means we's got you covered when it comes to clean data flows from source to model and working with tools such as Spark, Kafka and Snowflake or BigQuery. With Regards!