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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Engineer - **Company:** INFOCOMM INVESTMENTS US LLC - **Location:** Singapore, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Python (Programming Language), Machine Learning, SQL Databases, Management of Software Versions, Data Processing, Feature Engineering, Large Language Models, Apache Spark, Model Validation, Containerization, Kubernetes, Information Technology, Apache Kafka, Machine Learning Operations, Stream Processing, Software Version Control, Docker - **Published:** August 26, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pfdym6y2ox ## About the Role * Bachelor's, Master's, or PhD in Computer Science, Engineering, or a related field. * At least 5+ years of end-to-end and consistent building, deploying, and scaling machine learning models in production environments. * Hands-on experience productionising LLM-based systems. Bonus points for designing AI agents and multi-step workflows, tool/function calling, and grounding models on proprietary data through retrieval and context design - and treating prompts and model behaviour as engineering artifacts: versioning and prompt management, evaluation harnesses, guardrails, and monitoring output quality, latency and cost in live systems. We care about how you reason about system behaviour, reliability, and cost. * Proven experience across the full product lifecycle, taking models from R&D to deployment in fast-paced environments. * Experience in a product-based company, preferably a startup with early-stage technical product development. * Strong expertise in Python and SQL, with experience in cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). * Familiarity with real-time data processing, anomaly detection, and time-series forecasting in production. * Experience with large datasets and big data technologies like Spark and Kafka to build scalable solutions. * First-principles thinking and strong problem-solving, with a proactive approach to challenges. * A self-starter who takes ownership end to end and works autonomously to drive results. * Excellent communication, with the ability to convey complex technical concepts clearly and a strong customer-obsessed mindset. ## Description We are looking for a Senior Machine Learning Engineer who specializes in taking ML and AI models into production. You will own the full lifecycle, from research and model building to deployment and scaling in real-world environments. This is a hands-on role designing robust algorithms that address our core business problems, particularly in visibility, prediction, demand forecasting, and freight audit. Your focus is ensuring model accuracy, reliability, and scalability in live production systems. You'll be one of two on our data science team, so this role is built for someone highly independent, ambitious, and curious, comfortable owning problems end to end without a big team around them., * Develop and deploy machine learning models from initial research to production, ensuring scalability and performance in live environments. * Own the end-to-end ML pipeline: data processing, model development, testing, deployment, and continuous optimization. * Comfortable building from a rough outline rather than a finished spec. You'll work directly with product and customer-facing teams to turn loosely defined problems into shipped features, and re-scope quickly when priorities shift. You'll own the how, which means pushing back on a weak brief and making the call when the spec runs out. We have a strong sense of direction; the details pivot often. * Design and implement machine learning algorithms that address the key business problems our product focuses on: visibility, prediction, demand forecasting, and freight audit. * Ensure reliable, scalable ML infrastructure, automating deployment and monitoring using MLOps best practices. * Perform feature engineering, model tuning, and validation so models are production-ready and optimized for performance. * Build, test, and deploy real-time prediction models, maintaining version control and performance tracking. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Microservices: how to get started with Spring Boot and Kubernetes](https://www.wearedevelopers.com/videos/242-microservices-how-to-get-started-with-spring-boot-and-kubernetes) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)