AI Research Scientist

ABOUT CLIENT

Our client is a leading research company specializing in technology innovation

JOB DESCRIPTION

Driven by Intellectual Curiosity: Relentlessly explore the unknown, ask sharp questions, and challenge assumptions.
Constructively Combative: Engage in thoughtful debate to uncover truth, refine ideas, and push boundaries.
Experimental Mindset: Design and run AI experiments, analyze outcomes rigorously, and iterate with purpose.
User-Centered Innovation: Adapt AI systems to solve real-world problems and elevate the experience of Menlo's users.
Stay on the Cutting Edge: Continuously learn, absorb state-of-the-art research, and apply it with discernment.
Rapid Prototyping & Iteration: Ideate, implement, debug, and accelerate the cycle of experimentation and insight.
Robust Engineering: Build modular, maintainable training codebases that scale and evolve gracefully.
Efficient Data Infrastructure: Develop high-performance data loaders and utilities to streamline training workflows.
Scalable Training Systems: Architect jobs to run seamlessly across multi-GPU and multi-node setups (e.g., DDP, NCCL).
Performance Optimization: Tune models for speed, stability, and hardware efficiency without compromising accuracy.
Code Quality & Reproducibility: Write clean, testable, and reproducible code that stands the test of time.
Open Source Stewardship: Actively contribute to and improve the broader ecosystem through upstream collaboration.

JOB REQUIREMENT

Strong proficiency in PyTorch, including custom modules, loss functions, and distributed training
Demonstrated experience in training deep learning models in real-world research or production settings
Proficient engineering skills in Python, and optionally C++ for performance-critical components
Experience in working with large datasets, complex pipelines, and real-world debugging
Understanding of training dynamics and the ability to identify and resolve issues
Familiarity with job launchers, logging tools (e.g., Weights & Biases, TensorBoard), and checkpointing systems
Previous involvement with TorchScript, ONNX, or custom inference runtimes
Contributions to PyTorch or open-source ML tooling
Experience with transformer models, diffusion models, or large-scale vision/NLP tasks
Familiarity with batch schedulers (SLURM), cluster environments, and GPU resource management
Ability to collaborate closely with systems engineers or MLOps teams to ensure smooth integration

WHAT'S ON OFFER

Join a top-notch research team in working on impactful projects
Take ownership of and contribute to the development of the core training code infrastructure
Engage with real models, data, and scale, tackling substantial problems
Support in bridging the gap between research speed and engineering excellence
Enjoy a flexible work setup and a culture that promotes depth, clarity, and curiosity

CONTACT

PEGASI – IT Recruitment Consultancy | Email: recruit@pegasi.com.vn | Tel: +84 28 3622 8666
We are PEGASI – IT Recruitment Consultancy in Vietnam. If you are looking for new opportunity for your career path, kindly visit our website www.pegasi.com.vn for your reference. Thank you!

Job Summary

Company Type:

Product

Technical Skills:

Data Science

Location:

Others - Singapore

Working Policy:

Remote

Job ID:

J01854

Status:

Close

Related Job:

AI Software Transformation Engineer (Distributed Computing)

Ho Chi Minh - Viet Nam

Product

  • AI
  • Spark
  • Data Engineering
  • Backend

Create an advanced AI-powered software transformation framework to speed up the modernization of complex analytical applications. Develop architectural patterns and transformation methodologies for converting outdated computational tools into scalable cloud-native solutions. Utilize AI agents, LLMs, and emerging AI engineering techniques to automate software analysis, code transformation, validation, and optimization. Work with distributed computing specialists to design target architectures that leverage Spark-based execution models for large-scale data processing. Lead technical investigations into restructuring, decomposing, or re-implementing existing software systems for efficient operation in distributed environments. Develop reusable transformation pipelines, automation tooling, and engineering frameworks for large-scale software modernization. Establish validation strategies and quality frameworks to ensure that transformed systems maintain functional correctness and reproducibility. Make architectural decisions regarding scalability, maintainability, performance, and long-term platform evolution. Collaborate with domain experts to understand application requirements and translate them into scalable technical solutions. Prototype and assess new AI-assisted engineering approaches to enhance transformation speed, engineering productivity, and software quality. Contribute to the organization's long-term strategy for AI-driven software modernization and engineering automation.

Negotiation

View details

AI Automation Developer

Ho Chi Minh - Viet Nam

Product, Outsource

  • AI
  • Azure
  • NodeJS
  • ReactJS
  • Typescript
  • Devops

Create and implement GenAI-based applications across the client's operational processes Convert business needs into technical prototypes and operational applications Develop chat agents, copilots, and workflow automatons to enhance operational teams Leverage Microsoft Copilot Studio, Azure AI Services, and automation tools like Power Automate to craft scalable AI solutions Integrate GenAI features into existing systems and procedures Ensure responsible AI use, data accuracy, and compliance with internal security standards Keep abreast of new GenAI technologies, tools, and platforms through constant research and assessment Work collaboratively with various experts within operations, IT, and business units to document solutions and share knowledge across teams

Negotiation

View details

AI Agent Ops Engineer

Ho Chi Minh - Viet Nam

Product

  • AI
  • Backend

Responsible for the design, construction, and upkeep of production-grade AI agent systems, including areas such as context engineering, instruction architecture, secure execution boundaries, tool integrations, multi-step orchestration, memory strategies, and reliability patterns. Manage the complete lifecycle of agents from prototyping to deployment, monitoring, and iterating. Develop and maintain an evaluation pipeline to measure agent quality, identify regressions, and enforce deployment gates through the use of golden datasets, scenario suites, and automated checks. Instrument agents and agent platforms for production observability, such as structured logging, tracing, metrics, latency monitoring, cost monitoring, and analysis of tool-call success rates and failures. Establish operational readiness standards, including rollback criteria, incident response playbooks, and recovery paths for common failure modes. Collaborate with product engineering teams to identify high-value use cases suitable for agent automation, operating in a Central Agent Ops role to enable AI product builders through AI enablers. Translate business workflows into tasks executable by agents and provide coaching to engineers on context engineering best practices, harness design, regression testing patterns, agent skill design, and tool-contract discipline. Streamline the onboarding process for teams adopting AI capabilities and train product engineers to independently extend and maintain agent skills. Develop and maintain organizational standards for agents, including naming conventions, context file structures, skill interface contracts, evaluation criteria, and release quality benchmarks. Establish and enforce "repo-as-discipline" practices to ensure that agent knowledge is versioned, reviewable, discoverable, and reusable. Cultivate a shared agent skills library for teams to reuse and extend, while keeping track of AI tooling/framework updates and external best practices to provide centralized information to product teams. Facilitate internal knowledge-sharing sessions, showcases, and retrospectives to efficiently propagate learnings.

Negotiation

View details