Software Engineer, Metropolis Vision AI

ABOUT CLIENT

Our client is a leading technology company specializing in graphics processing units (GPUs) and artificial intelligence (AI).

JOB DESCRIPTION

Developing advanced Metropolis Vision AI pipelines using computer vision and deep learning models for real-time and streaming applications.
Building distributed services to process video, image, and 3D data in both edge and cloud environments.
Enhancing multi-modal perception capabilities to understand complex real-world scenes by combining 2D, 3D, and temporal information.
Utilizing simulation and synthetic data tools for building, testing, and validating perception algorithms at scale.
Optimizing GPU-accelerated inference pipelines to meet specific latency, efficiency, and reliability requirements.
Working with partner teams on technical implementations.
Contributing to technical reviews and guidelines for code quality and testing.

JOB REQUIREMENT

Completed a BS or MS in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
Held a professional software development role for at least 2 years with modern C++ (14/17/20) and Python on Linux.
Possess robust computer science knowledge, including algorithms, data structures, concurrency, and distributed systems concepts.
Have experience in computer vision and deep learning.
Have experience in implementing concurrent systems and Linux-based environments with containers and microservices, integrating AI components into scalable back-end services.
Have practical experience using PyTorch in training, fine-tuning, and deploying models for vision tasks.
Strong analytical and problem-solving skills, with a data-driven approach to performance optimization and system build.
Excellent written and verbal English communication skills, with demonstrated success collaborating across time zones and functions.
Practical experience implementing end-to-end computer vision applications in production, such as video analytics, smart cities, autonomous systems, retail analytics, industrial inspection, or digital twins.
Practical experience with low-level optimization for inference and pre/postprocessing.
Experience in simulation and synthetic data creation employing tools such as
Omniverse, Unreal Engine, Unity, or similar digital-twin platforms.
Background in multimedia, including video-centric processing and delivery (such as codecs, video pipelines, or media frameworks) and integrating vision models into multimedia workflows.

WHAT'S ON OFFER

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:

C/C++, Python, AI

Location:

Ho Chi Minh - Viet Nam

Working Policy:

Hybrid

Job ID:

J02057

Status:

Close

Related Job:

Lead Software Engineer (Distributed Computing)

Ho Chi Minh - Viet Nam

Product

  • Data Engineering
  • Backend
  • Spark
  • AI

Translate business objectives to technical solutions. Lead R&D to discover novel approaches and propose technical solutions. Lead the design and development of a next-generation AI-powered software transformation framework capable of accelerating the modernization of complex analytical applications. Own key architectural decisions for converting legacy computational tools into scalable cloud-native solutions. Define technical direction, engineering standards, and transformation methodologies for AI-assisted software modernization. Guide the use of AI agents, LLMs, and emerging AI engineering techniques to automate software analysis, code transformation, validation, and optimization. Lead technical investigations into how existing software systems can be restructured, decomposed, or re-implemented to operate efficiently in distributed environments. Collaborate with distributed computing specialists to design target architectures using Spark-based execution models for large-scale data processing. Build and guide the development of reusable transformation pipelines, automation tooling, and engineering frameworks that enable software modernization at scale. Establish validation strategies, quality frameworks, and technical review processes to ensure transformed systems maintain functional correctness and reproducibility. Drive architectural decisions around scalability, maintainability, performance, infrastructure efficiency, and long-term platform evolution. Mentor senior and mid-level engineers, review technical designs, and raise the engineering quality of the team. Partner with domain experts to understand application requirements and translate them into scalable, practical technical solutions. Prototype and evaluate new AI-assisted engineering approaches that improve transformation speed, engineering productivity, and software quality. Contribute to the organization's long-term strategy for AI-driven software modernization, distributed computing, and engineering automation.

Negotiation

View details

Head of Engineering

Da Nang - Viet Nam

Product

  • NodeJS
  • NestJS
  • ReactJS
  • Typescript
  • AWS
  • AI

Develop and communicate the engineering strategy, technical roadmap and priorities that align with product goals, customer outcomes and regulatory obligations. Assume responsibility for various aspects of the engineering process including discovery, estimation, architecture, development, testing, release, production support, incident response and continual improvement. Establish and build the engineering organisation by defining team structure and roles, participating in hiring, coaching and retaining engineers, and creating clear expectations and development paths. Lead internal engineers and oversee external engineering delivery partners to ensure agreed outcomes, quality standards, security requirements, and delivery commitments are met. Maintain a strong technical understanding to challenge designs, lead architecture and code reviews, resolve complex issues, and make informed decisions. Establish and enforce engineering standards for secure software development, code quality, automated testing, release management, and technical debt reduction. Assume responsibility for production reliability and operational readiness, including observability, capacity, availability, performance, incident management, and root-cause remediation. Integrate security and privacy into the engineering process, including encryption, auditability, secrets management, vulnerability remediation and data minimization. Collaborate with other teams to shape requirements, manage trade-offs, communicate risk and provide transparent delivery forecasts. Define measurable engineering objectives and own responsible AI adoption across various areas. Evaluate AI-enabled product opportunities and manage engineering suppliers and technology vendors. Contribute to budgeting, forecasting and prioritization, ensuring engineering expenditure produces measurable business value.

Negotiation

View details

Salesforce Engineer (IC2)

Ho Chi Minh - Viet Nam

Outsource

  • Salesforce

#Salesforce Engineering (Quote-to-Cash) Build and maintain Salesforce processes from Quote through to Cash Work full-stack on the platform: declarative (data model, Flows, validation, security model) and programmatic (Apex, Lightning Web Components) Implement changes safely on a production system used by Go-to-Market every day#Integrations & System Interfaces Maintain and further develop the integrations between Salesforce and internal/external systems (customer portal, HubSpot, license management, billing/ERP, and others) Design and operate integrations using Salesforce REST/SOAP APIs and standard integration patterns Own the health of these interfaces: monitoring, error handling, and data consistency#Collaboration with Go-to-Market / RevOps Partner with RevOps and GTM to translate business needs into robust technical implementations Challenge requirements where they create risk or technical debt Coordinate handoffs at the Lead-to-Quote / Quote-to-Cash boundary#Reliability, Security & Change Safety Protect a revenue-critical system: change control, testing, backup/rollback awareness Apply JTL security and compliance standards to Salesforce work#Optional / stretch With spare capacity, support tech-heavy Lead-to-Quote topics in Salesforce (optional; primary ownership of Lead-to-Quote stays with RevOps)

Negotiation

View details