# Technical Lead (Machine Learning)

> Avomind · Singapore (Remote) · Full-time · Posted 2026-07-27

**Workplace:** remote

**Department:** External - Technology

## Description

### About the Company

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

The company is developing an AI-native 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 within 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-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive.

### About the Role

Our client is seeking a **Technical Lead, Machine Learning** to lead the execution of its AI platform by translating research into scalable, production-ready 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 real-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

-   Lead 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 **LoRA, QLoRA, Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and model distillation**.
-   Design, build, and operate scalable inference systems with a focus on latency, cost efficiency, and reliability.
-   Develop and maintain data pipelines for both synthetic and real-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 integrate 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 real users.
-   Strong expertise working with large language models and understanding model behavior, limitations, and failure modes.
-   Experience developing scalable ML infrastructure, training pipelines, and inference systems.
-   Strong software engineering skills with the ability to write maintainable, production-quality code.
-   Experience balancing real-world production constraints, including latency, reliability, scalability, cost, and safety.
-   Strong ownership mindset 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

## Apply

[Apply at Avomind](https://apply.workable.com/avomind/j/639154C928/apply)

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