AI Research Engineer

J
oin Us!

Amity, through its AI Research and Application Center, is advancing the frontier of applied AI research across natural language processing, large language models, agentic systems and generative AI. We build intelligent products that serve millions of users and partner organisations across Southeast Asia and Europe. Our research engineers sit at the intersection of scientific inquiry and production engineering—discovering new methods, validating them rigorously, and shipping them into real-world products.

Your Impact:

As an AI Research Engineer at Amity AI Research and Application Center you will own ambitious research goals while ensuring that breakthroughs translate into scalable, production-grade systems.

You will:

• Identify high-impact research problems, formulate hypotheses, design experiments and advance the state of the art in areas aligned with the lab’s mission.
• Publish findings at top-tier conferences and top-tier leader board and contribute to the broader AI research community.
• Bridge the gap between research prototypes and production systems, ensuring novel methods are robust, efficient and deployable at scale.
• Shape the lab’s research roadmap and propose initiatives that create measurable business and societal value.
• Mentor junior researchers and engineers, fostering a culture of scientific rigour and collaborative innovation.

Your Day-to-Day:

Research & Experimentation

• Conduct original research in one or more areas:
  large language models
  , NLP, computer vision, reinforcement learning, generative models, agentic AI or multimodal learning.
• Design and run rigorous experiments—including ablation studies, benchmark evaluations and statistical analyses to validate new methods and architectures.
• Survey, reproduce and extend state-of-the-art results from recent literature; maintain a reading group culture within the team.
• Develop novel algorithms, model architectures and training strategies that push performance boundaries on real-world tasks.

Model Development & Optimisation

• Design, train and fine-tune large-scale deep learning models (LLMs, diffusion models, multi-modal models) using modern frameworks such as PyTorch, TRL, Unsloth or verl. (Reinforcement Learning Experience is plus)
• Optimise model performance through techniques such as knowledge distillation, quantisation, pruning, mixed-precision training and efficient attention mechanisms.
• Build and improve training infrastructure for distributed, large-scale model training across GPU/TPU clusters.
• Develop evaluation frameworks and metrics to systematically measure model quality, safety and robustness.

Applied Research & Productionisation

• Translate research outcomes into production-ready features—building proof-of-concepts (PoCs), prototypes and scalable AI services.
• Design and operate RAG pipelines (ingestion, chunking, embeddings, hybrid search, re-rankers) with vector databases (pgvector, Pinecone, Weaviate, Open Search) to support retrieval-augmented applications.
• Architect and ship LLM-powered agents and chatbots using agentic patterns (tool/function calling, planning, memory, multi-agent orchestration) with robust safety and fallback mechanisms.
• Collaborate with product and engineering teams to integrate AI capabilities into customer-facing platforms via APIs and microservices.

Data & Infrastructure

• Curate, clean and build high-quality datasets for pre-training, fine-tuning and evaluation; design data pipelines for continuous data collection and annotation.
• Implement and maintain scalable ML infrastructure using Docker, Kubernetes, CI/CD and experiment-tracking tools (MLflow, Weights & Biases, or similar).
• Monitor deployed models, design automated retraining pipelines and ensure ongoing model quality through observability and alerting.

Knowledge Sharing & Community

• Author technical papers, internal reports and blog posts that communicate research findings to both technical and non-technical audiences.
• Present research at internal seminars, external conferences and community meetups.
• Contribute to open-source projects and public benchmarks to enhance Amity’s visibility in the research community.

Your Ideal Profile:

Required

• Education: Master’s or Ph.D.…