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

Salary:

Negotiation

Job ID:

J01854

Status:

Active

Related Job:

Senior Data Engineer

Ho Chi Minh - Viet Nam

Product

Designing and implementing scalable data architectures aligned with business objectives Building and maintaining data pipelines for ingestion, transformation, and delivery using modern orchestration tools Architecting data solutions across data warehousing, data lakes, and real-time analytics Creating and maintaining data models and documenting the enterprise data landscape Building and maintaining data infrastructure supporting ML model training, deployment, and monitoring Designing and implementing vector database solutions for AI-powered features Developing data pipelines for AI-driven capabilities and ensuring global scalability Implementing DataOps practices to ensure data quality, lineage, and governance Defining and enforcing data strategy and architectural principles Building monitoring and alerting for pipeline health, data quality, and SLA compliance Optimizing query performance and cost efficiency Collaborating with product and engineering teams to translate business requirements into data solutions Driving adoption of modern data practices across the organization Contributing to architectural reviews and technical decision-making Taking ownership of data problems through to resolution

Negotiation

View details

Data Analyst

Ho Chi Minh - Viet Nam

Offshore

  • Data Analyst

Gather, sanitize, and evaluate data from diverse origins to meet business requirements. Construct and maintain fundamental analytical datasets and reports for different teams. Validate and verify data to uphold accuracy, consistency, and dependability. Apply statistical and analytical methods to identify patterns and potential opportunities. Work closely with business stakeholders to grasp needs and provide actionable insights. Carry out thorough analyses of customer behavior, product usage, and market trends. Translate intricate data findings into clear, influential recommendations for business strategies. Support data-informed decision-making across various teams including marketing, operations, finance, and product teams. Create dashboards and Key Performance Indicator (KPI) tracking tools for monitoring business performance. Devise and conduct experiments (e.g., A/B tests) to evaluate initiatives. Deliver insights in a clear and convincing manner to both technical and non-technical audiences. Encourage data literacy by aiding colleagues in understanding and utilizing analytical tools. Share best practices in data analysis, visualization, and reporting. Contribute to documentation and training to elevate organizational analytics proficiency. Allocate time to cross-team projects aimed at enhancing company-wide data capabilities.

Negotiation

View details

Engineering Manager (Data Platform)

Ho Chi Minh - Viet Nam

Offshore

  • Data Engineering
  • Management

Agile Team Leadership: Guide and coach Agile teams to uphold engineering standards, manage sprint backlogs, clarify responsibilities, ensure code quality, enforce development guardrails, and drive rigorous testing practices. Agile Data Delivery: Oversee Agile execution across data platforms, maintaining excellence in data quality, testing, code review practices, CI/CD pipelines, documentation, and operational readiness. Cross-Functional Collaboration: Partner with data architects, product managers, analytics teams, platform engineers, and governance stakeholders to deliver data capabilities aligned with business priorities. Roadmap Ownership: Lead the execution of the data engineering roadmap, balancing immediate delivery needs with long-term platform sustainability. Architecture & Design: Contribute to the design of data platform architecture across ingestion, transformation, storage, and consumption layers. Engineer Development: Coach engineers to become T-shaped professionals, capable of working across batch processing, streaming, analytics engineering, and platform operations. Technical Debt Remediation: Own and prioritize the resolution of technical and data debt, including legacy pipelines, performance bottlenecks, and data quality issues. Modern Practices: Stay current with evolving data engineering tools, methodologies, and patterns-particularly within the Databricks ecosystem. Lifecycle Accountability: Ensure end-to-end ownership of data solutions, from design and build through deployment, monitoring, and ongoing support. Team Empowerment: Foster self-sufficient, disciplined teams accountable for the reliability and resilience of data products. Process Excellence: Lead initiatives to enhance data delivery through automation, observability, and operational best practices. Continuous Improvement: Inspire teams to innovate, experiment, and embrace continuous delivery as part of their culture. Career Growth: Drive career development for data engineers, partnering with HR to manage performance and define growth pathways.

Negotiation

View details