Bitdeer is hiring a Senior Inference Runtime Engineer in AI Cloud — Singapore, SG. The overview below is synthesized from the employer posting on bitdeer.breezy.hr: factual requirements and scope are preserved, but prose is rewritten with editorial context. Verify details and apply via the employer link.
About Bitdeer
Company context from the listing:
Bitdeer is a world-leading technology company for Bitcoin mining and AI cloud.
Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers. Apart from designing industry-leading ASIC chips and manufacturing mining rigs, the Group handles complex processes involved in computing across the value chain.
Headquartered in Singapore, Bitdeer operates globally with a diversified 3 GW energy portfolio, and deploys Bitcoin mining and HPC datacenters in the United States, Bhutan, Norway, Canada, Malaysia, and Ethiopia.
About the team：
Company context from the listing:
The listing frames the Senior Inference Runtime Engineer at Bitdeer as a hands-on product role. This role focuses on making self-hosted LLMs faster, cheaper, and more stable by optimizing the runtime stack behind OpenAI- and Anthropic-compatible APIs.
What you will be responsible for
- Optimize prefill/decode scheduling, continuous batching, KV cache behavior, speculative decoding, long-context serving, and streaming smoothness.
- Tune and operate vLLM/Dynamo/SGLang/TensorRT-LLM-style runtimes for model-specific latency, throughput, GPU utilization, and cost efficiency.
- Profile bottlenecks across GPU memory, HBM bandwidth, NCCL/network, tokenizer, frontend/proxy, and model worker paths.
- Lead high-value model onboarding, including runtime selection, tensor/pipeline parallelism, quantization, context length, and rollback strategy.
- Define runtime playbooks and safe defaults for reasoning, tool calling, multimodal, prompt cache, and provider-specific parameters.
- Partner with SRE and performance/evaluation engineers to turn benchmark findings into production runtime improvements.
How you will stand out:
- 6+ years of systems, ML infrastructure, or high-performance backend engineering experience.
- Hands-on experience with LLM serving runtimes such as vLLM, Dynamo, SGLang, TensorRT-LLM, TGI, or Triton.
- Strong understanding of GPU memory, CUDA/NCCL basics, KV cache, batching, streaming, and distributed inference tradeoffs.
- Proficient in Go or Python and comfortable reading runtime source code, profiling traces, and production metrics.
- Experience operating production inference services with strict latency, availability, and cost targets.
- Able to translate low-level performance work into customer-visible reliability, latency, and margin improvements.
What you will experience working with us
- A culture that values authenticity and diversity of thoughts and backgrounds;
- An inclusive and respectable environment with open workspaces and exciting start-up spirit;
- Fast-growing company with the chance to network with industrial pioneers and enthusiasts;
- Ability to contribute directly and make an impact on the future of the digital asset industry;
- Involvement in new projects, developing processes/systems;
- Personal accountability, autonomy, fast growth, and learning opportunities;
- Attractive welfare benefits and developmental opportunities such as training and mentoring.
Bitdeer is committed to providing equal employment opportunities in accordance with country, state, and local laws. Bitdeer does not discriminate against employees or applicants based on conditions such as race, colour, gender identity and/or expression, sexual orientation, marital and/or parental status, religion, political opinion, nationality, ethnic background or social origin, social status, disability, age, indigenous status, and union.
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Build a standout application
For the Senior Inference Runtime Engineer at Bitdeer, reviewers look for concise evidence over buzzwords. Mirror the language of the posting sparingly, quantify support or delivery outcomes, and show how you handled ambiguity, time-zone collaboration and user empathy. Keep your resume to impact, keep your cover note to one page, and link to artifacts — tickets resolved, docs shipped, dashboards owned — that prove you can operate in a fast-moving Web3 team. Prepare to discuss a time you turned a confusing user report into a clear fix and how you measure quality in support and operations.
Web3 hiring values reliability: on-time follow-through, clear writing, and a track record of improving runbooks and tooling. Treat the application as a work sample. For interviews, be ready to walk through how you prioritize across time zones, handle a difficult user, and decide when to escalate versus resolve directly. Show how you document decisions so the next teammate benefits.
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