Distributed Systems Engineer

ABOUT CLIENT

Our client is a leading research company specializing in technology innovation

JOB DESCRIPTION

Design and create distributed systems capable of handling large amounts of sensory, telemetry, and control data across cloud and edge environments.
Plan and implement data ingestion and streaming pipelines to connect groups of robots to the cloud in real-time (video, LiDAR, joint states, audio).
Construct platforms for extensive training and inference to support robot autonomy and teleoperation using foundation models.
Work closely with ML and Robotics engineers to assist in hardware-in-the-loop simulation, policy rollout, and continuous learning initiatives.
Create internal observability systems to monitor fleet performance, reliability, and tuning.
Take the lead on infrastructure decisions such as distributed storage, consensus protocols, GPU orchestration, and network reliability.

JOB REQUIREMENT

Must have more than 7 years of professional experience in software engineering, specializing in distributed systems, networking, or data infrastructure.
Demonstrated capability in constructing and maintaining distributed systems that can handle large-scale workloads.
Proficient in Go, Rust, C++, or Python, with a strong foundation in concurrency, networking, and systems performance.
Familiarity with cloud-native architectures such as Kubernetes, gRPC, Kafka, S3, Ray, or similar frameworks.
Thorough understanding of data consistency, replication, and fault tolerance in heterogeneous environments.
Experience in GPU-based workloads, model training, or edge compute orchestration is desirable.
Strong analytical skills and a preference for developing fast, measurable, and dependable systems.
Experience in creating distributed training or large-scale simulation systems.
Knowledge of real-time robotics workloads, including streaming from physical sensors and actuators.
Previous involvement with telemetry, observability, or fleet-scale systems in production.
Contributions to open-source infrastructure, AI frameworks, or robotics middleware (ROS, gRPC, Mediasoup, etc.) would be advantageous.

WHAT'S ON OFFER

Join an exceptional research team to work on significant and impactful projects
Take charge of and influence the primary training code infrastructure utilized by the team
Engage with actual models, real data, and substantial scale challenges, not small-scale problems
Contribute to bridging the gap between research speed and engineering excellence
Enjoy a flexible work setting with a culture that treasures depth, transparency, and inquisitiveness

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 Engineering, Devops, Golang, Rust, C/C++, Python

Location:

Others - Viet Nam

Working Policy:

Onsite, Remote

Job ID:

J01893

Status:

Close

Related Job:

AI Engineer Lead

Ho Chi Minh - Viet Nam

Outsource

  • AI
  • Python

Spearhead the development and deployment of various applications, pipelines, and workflows tailored for financial services applications. Take charge of critical technical determinations related to model choices, design of retrieval systems, workflow structuring, integration strategies, cost considerations, and latency issues. Develop methodologies for evaluation and regression testing, utilizing data analysis and failure diagnostics to enhance the effectiveness of solutions. Ensure that deployed solutions adhere to production standards encompassing reliability, security, observability, data security, and audit trails. Transform business, risk, and compliance prerequisites into actionable technical solutions in collaboration with clients and internal partners. Provide guidance to engineers, fostering the adoption of standardized AI engineering practices, frameworks, and development methodologies.

Negotiation

View details

Senior Engineer Manager - Technology Risk

Ho Chi Minh - Viet Nam

Product

  • Management
  • Backend
  • Data Engineering
  • Devops

Develop and implement a cohesive roadmap for strategic execution based on the company's strategic ambitions Coordinate and oversee multiple engineering teams within the organization to achieve desired outcomes Collaborate with various internal teams, including technology, risk, business, and product teams, to ensure requirements are met before and after project delivery Take responsibility for both the development and ongoing operational support of applications in production Manage cyber security updates, ensuring software versions are up to date and infrastructure is patched regularly Monitor and control investment delivery to maintain alignment between different domains and optimize spending Facilitate collaboration between engineering and risk domain experts to achieve strategic technology goals

Negotiation

View details

Data Engineer

Ho Chi Minh - Viet Nam

Outsource

  • Data Engineering
  • Python

Develop, test, and manage batch and streaming data pipelines on various cloud platforms like Snowflake, AWS Redshift, and Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, Cloud Composer). Import data from various sources such as client APIs, SaaS platforms, event streams, and databases into secure cloud storage and warehouse layers. Create transformation logic using SQL and Python and deploy tested, well-documented models in dbt. Establish datasets and dashboards in Sigma for easy querying by business users and AI systems. Prepare and deliver data for AI applications, including feature tables, embeddings, and retrieval datasets, and provide access to data through controlled APIs and MCP servers. Utilize AI programming tools and automated workflows to enhance development efficiency, testing, and documentation, ensuring accuracy in the output. Set up data quality assessments, monitoring, and alerts, and develop automated procedures for diagnosing pipeline failures with AI support. Record details about pipelines, schemas, and data structures for the benefit of other teams and AI systems. Engage in code assessments and sprint planning within an agile, globally distributed team.

Negotiation

View details