MLOps Engineer

JOB DESCRIPTION

Be a part of building the ideal data and ML/AI ecosystem from scratch. Spearheaded the integration of the latest capabilities to enhance customer experiences and transform business operations. Embrace the vision of democratizing ML/AI technology, making it accessible to all by establishing robust engineering standards, simplifying complexities, and designing effective controls and guardrails. This leadership role goes beyond conventional boundaries, empowering you to lead and innovate across many aspects of our data enablement value stream.
Your role as an MLOps Engineer will be similar to a DevOps engineer, with a stretched focus on productionizing Machine Learning features:
Design and implement scalable AI solutions that enables data engineers and ML scientists to train, build, and maintain machine learning models effectively.
Develop automated processes for continuous model training and evaluation pipelines specifically for ML applications.
Ensure the seamless integration of Company Plus's current architecture with newly added ML functionalities, enhancing overall system capabilities.
Collaborating with diverse stakeholders including business partners, risk, legal, and security teams, as well as UX designers and architects to define and implement robust validation and verification strategies
Fostering a culture of quality coding practices, including test-driven development, unit testing, and secure coding awareness
Focus on business practicality and the 80/20 rule, aiming for a high bar for code quality, but recognize the business benefit of "having something now" vs "perfection sometime in the future"

JOB REQUIREMENT

To grow and be successful in this role, you will bring extensive analytical and technical skills, business acumen and natural curiosity to deliver on product investigations and analysis and support initiatives through insights.
You will ideally bring the following:
Proficiency in one of the scripting/programming languages (Python).
Experience in building data products using GCP/ AWS technologies.
Experience with containerization, Terraform, and GitOps principles for automation and deployment.
Strong background in ML concepts and applications and in-depth knowledge of MLOps best practices.
Agile development mindset, appreciating the benefit of constant iteration and improvement.
Have experience in addressing Tech Debt with minimizing production incidents.
Familiarity with RAG architectures and/or have a good understanding of their application.

WHAT'S ON OFFER

Attractive package including fixed 13-month salary and variable performance bonus
Insurance plan based on full salary
100% full salary and benefits as an official employee from the 1st day of working
Medical benefit (private insurance) for employee and their family
18 paid leaves/year (12 annual leaves and 6 personal leaves)
Working in a fast-paced, flexible, and multinational working environment.
Chance to travel for business trip in foreign countries
Free snacks, refreshment, and parking
Career development in a giant tech hub just entering Vietnam market, with very challenging project
Hybrid working mode, flexible time (3 days in office per week)

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:

Outsource

Technical Skills:

Machine Learning, Devops, Data Science, Python, Java

Location:

Ho Chi Minh - Viet Nam

Working Policy:

Salary:

Negotiation

Job ID:

J01554

Status:

Close

Related Job:

Senior Deep Learning Algorithms Engineer

Ho Chi Minh, Ha Noi - Viet Nam


Product

  • Machine Learning
  • Algorithm

Analyze and optimize deep learning training and inference workloads on advanced hardware and software platforms. Work with researchers and engineers to enhance workload performance. Develop high-quality software for deep learning platforms. Create automated tools for workload analysis and optimization.

Negotiation

View details

Software Engineer

Ho Chi Minh - Viet Nam


Product

Create and develop the API Platform with a focus on reliability, performance, and providing a top-tier developer experience Deploy and enhance AI/ML models in scalable, production environments in collaboration with research and applied ML teams Manage and advance a contemporary, cloud-native infrastructure stack utilizing Kubernetes, Docker, and infrastructure-as-code (IaC) tools Ensure platform dependability by designing and implementing telemetry, monitoring, alerting, autoscaling, failover, and disaster recovery mechanisms Contribute to developer and operations workflows, encompassing CI/CD pipelines, release management, and on-call rotations Work collaboratively across teams to implement secure APIs with fine-grained access control, usage metering, and billing integration Continuously enhance platform performance, cost-efficiency, and observability to accommodate scaling and serve users globally.

Negotiation

View details

Product Manager (Data & Models)

Ho Chi Minh - Viet Nam


Product

  • Product Management
  • AI

Designing data strategy and model integration for creating efficient data pipelines, evaluation frameworks, and annotation systems to maintain high-performance LLMs. Responsible for ensuring data quality standards and implementing bias mitigation and privacy-preserving techniques. Defining the product's core model roadmaps, taking into account technical feasibility, user needs, and ethical considerations. Collaboration with researchers to incorporate experimental breakthroughs into deployable features. Partnering with Engineering and Research teams to ensure model development aligns with product goals and advocating for transparency in model decision-making to build user trust. Analyzing usage patterns from open-source communities (Discord, Reddit, GitHub) to refine model behavior and address real-world edge cases, contributing to community-driven model evolution. Setting performance benchmarks, cost efficiency, and resource utilization standards for model scalability and reliability.

Negotiation

View details