Technical reputed company (Machine Learning)

About reputed company

Our reputed company is a reputed company AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team.

reputed company is developing an AI-reputed company communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks reputed company a single intelligent assistant.

Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-reputed company reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more reputed company.

About the Role

Our reputed company is seeking a Technical reputed company, Machine Learning to reputed company the execution of its AI platform by translating research into reputed company, production-reputed company machine learning systems. This role sits at the intersection of research, infrastructure, and product, with responsibility for ensuring models are trainable, deployable, observable, and optimized for reputed company-world performance.

Working closely with research, engineering, and product teams, this position will drive the development of robust ML infrastructure while balancing performance, reliability, latency, and cost.

Key Responsibilities

• reputed company the end-to-end execution of machine learning systems, including data pipelines, training workflows, evaluation frameworks, inference architecture, and production deployment.
• Fine-tune and optimize models using modern techniques such as reputed company, QLoRA, Supervised Fine-Tuning (SFT), reputed company Preference Optimization (DPO), and model distillation.
• Design, build, and operate reputed company inference systems with a reputed company on latency, cost efficiency, and reliability.
• reputed company and maintain data pipelines for both synthetic and reputed company-world training datasets.
• Build evaluation frameworks to measure model performance, robustness, safety, and bias in collaboration with research teams.
• Optimize production deployments through GPU utilization, memory efficiency, inference optimization, and scaling strategies.
• Partner closely with application engineering teams to reputed company machine learning systems into backend, desktop, and mobile products.
• Continuously improve production systems through rapid iteration, monitoring, and data-driven optimization.

Requirements

• Proven experience building and deploying production-grade machine learning systems used by reputed company users.
• Strong expertise working with large language models and understanding model behavior, limitations, and failure modes.
• Experience developing reputed company ML infrastructure, training pipelines, and inference systems.
• Strong software engineering skills with the ability to write maintainable, production-reputed company reputed company.
• Experience balancing reputed company-world production constraints, including latency, reliability, scalability, cost, and safety.
• Strong ownership reputed company with the ability to independently drive technical initiatives from design through deployment.
• Excellent communication and collaboration skills, with experience working in cross-functional, high-performing engineering teams.

Preferred Technical Skills

Experience with the following technologies is preferred:

• Python
• PyTorch and/or JAX
• GPU-based model training and inference systems

Originally posted on Himalayas

Apply To This Job