HPC & Cloud Infrastructure Engineer

Important Information

Location: Singapore

12 months contract

Job Summary

We’re hiring an HPC & Cloud Infrastructure Engineer to design, deploy, and optimize high-performance computing environments across on-prem and cloud. You’ll manage HPC clusters, interconnects, job schedulers, and enable AI/ML workloads at scale while driving automation and cost efficiency

Job Description

Architect, deploy, and manage HPC clusters with job schedulers, parallel file systems, and cluster management tools

Design, configure, and troubleshoot Infiniband high-throughput, low-latency interconnects for HPC/distributed workloads

Own PBS Professional scheduling: deployment, queue optimization, custom job submission scripts, workload management

Administer RHEL-based systems: performance tuning, package management, security hardening, patching via Red Hat Satellite and Ansible

Build and maintain cloud HPC environments on AWS, Azure, and GCP – provisioning, hybrid setups, migrations, and cost optimization

Implement Infrastructure as Code using Terraform/Ansible and integrate with CI/CD pipelines for reproducible infrastructure

Enable GPU & AI/ML workloads: containers, TensorFlow, PyTorch, scikit-learn, Keras, MXNet; support MLOps pipelines for training and deployment

Optimize parallel applications using MPI and OpenMP; debug and scale distributed/shared memory workloads

Drive monitoring, logging, and alerting for cluster health, job efficiency, and resource utilization

Required Skills and Experience

High-Performance Computing

Hands on experience in managing HPC clusters with job scheduler, cluster management parallel programming libraries, and parallel filesystems.

Knowledge of resource scheduling and job optimization for efficient workload management

Infiniband (Networking)

Hands-on experience with high-throughput, low-latency interconnect technologies like Infiniband.

Ability to design, configure, and troubleshoot interconnects in HPC or distributed environments.

Operating Systems and Environments 

Administration and configuration of RHEL-based systems.

Performance tuning, package management, and security hardening.

Knowledge of Red Hat Satellite and Ansible for automation.

Job Scheduling with PBS Professional 

Experience in deploying and managing PBS Professional for scheduling and workload management in HPC environments.

Customizing job submission scripts and optimizing job queues.

Parallel Programming Libraries

MPI (Message Passing Interface) and OpenMP (Open Multi-Processing):

Proficiency in writing, debugging, and optimizing parallelized code.

Experience with scaling applications across HPC systems.

Understanding of distributed memory (MPI) and shared memory (OpenMP)

paradigms.

Cloud Platforms

AWS, Azure, Google Cloud:

Expertise in provisioning, configuring, and managing services on all three platforms.

Cross-platform migration and hybrid cloud solutions knowledge.

Proficiency in managing high-performance computing (HPC) clusters on the cloud.

Deep understanding of cost optimization, security, and cloud native development tools (e.g., Kubernetes, Terraform).

Infrastructure as Code (IaC) 

Ability to design, deploy, and maintain infrastructure using automation and configuration management tools.

CI/CD pipeline integration for IaC workflows.

GPU & AI Libraries and Tools 

Hands-on experience with container technologies.

Hands-on experience with TensorFlow, PyTorch, scikit-learn, Keras, or MXNet.

Familiarity with AI/ML pipelines, model training, and optimization.

Knowledge of MLOps tools for deploying and monitoring models

About Encora

Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others.

At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

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Mission

The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. 

The impact you will have:

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI research to solve customer problems
• Own production rollouts of consumer and internally facing GenAI applications
• Serve as a trusted technical advisor to customers across a variety of domains
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap 

What we look for:

• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations 
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving business value through AI
• [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets
• We require fluency in English and have a preference for candidates who also speak Mandarin

Work you’ll do

As an AI Engineer at SimplifyNext, you will be part of a hands-on engineering team building real-world AI and machine learning solutions that create meaningful impact for clients across ASEAN. You will work closely with consultants, architects, and domain experts to translate business problems into deployable AI models, generative AI workflows, and intelligent automation components.

You will have the opportunity to experiment with modern AI frameworks, build prototypes, fine-tune models, and implement AI capabilities end-to-end—from data preparation to deployment. This role is designed for fresh graduates who want to build, break, learn, and innovate within a supportive environment grounded in consulting excellence and deep engineering capability.

Your responsibilities would include but not limited to:

AI & Machine Learning Development

· Build and train machine learning models using Python and modern ML frameworks

· Experiment with generative AI technologies (LLMs, embeddings, prompt engineering, RAG, agentic workflows)

· Support fine-tuning, optimisation, and evaluation of AI models

· Develop reusable AI components and microservices

Data Engineering & Preparation

· Collect, clean, and transform datasets for training and inference

· Perform exploratory data analysis to uncover patterns and insights

· Document data assumptions, limitations, and preprocessing logic

Solution Engineering

· Contribute to AI solution design, model selection, architecture discussions, and implementation approaches

· Integrate AI models into applications, APIs, and automation workflows

· Build proof-of-concepts (POCs) and accelerate client adoption of AI

Testing, Deployment & Delivery

· Conduct model validation, scenario testing, and UAT with internal and client stakeholders

· Support deployment of AI models on cloud platforms (AWS/GCP/Azure) or containerised environments

· Monitor performance and support continuous improvement post-deployment

Collaboration & Consulting Exposure

· Work with functional SMEs to understand business problems and AI opportunities

· Translate complex concepts into simple, understandable terms for non-technical audiences

· Participate in workshops, demos, and client discussions as part of project teams

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, AI, Data Science, or a related field.

• 0–3 years of AI development experience (Fresh graduates are welcome to apply)

• Strong foundation in Python, algorithms, and data structures

• Familiarity with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or HuggingFace

• Understanding of ML fundamentals: supervised/unsupervised learning, model evaluation, feature engineering

• Knowledge of cloud platforms (AWS, GCP, Azure) is a plus

• Familiarity with Git, REST APIs, or notebook-based development is beneficial

• Strong analytical thinking, curiosity, and problem-solving skills

• Passion for AI, experimentation, building things, and delivering quality work

Why Join Us

· Be part of a fast-growing consulting and technology firm driving AI, automation, and next-gen engineering

· Work on high-impact challenges across ASEAN, delivering real-world AI solutions

· Gain hands-on experience from day one with industry experts, architects, and consultants

· Contribute to innovation programmes, accelerators, and AI Centres of Excellence

· Grow rapidly through certifications, mentorship, structured enablement, and exposure to emerging AI technologies

· Join a supportive, high-trust culture that values creativity, experimentation, and continuous learning