Featherless AI
More roles at Featherless AIAI Researcher — Inference Optimization
Remote work allowed only within certain countries or regions.
Employer listed it 9 months ago · Added 5 weeks ago
Been open since 9 months ago. Long-running listings are sometimes left up after the role is filled.
Salary
Not stated
Location
Timezone
Not stated
Contract
Full-time
Experience
Mid
Category
Other
The employer did not publish a salary, and we have too few comparable roles to estimate one.
What the advert says
Quoted word for word from the employer's advert. Where it says nothing, we say so.
- Working hours
- Not mentioned in the advert
- Where you can work from
- Location eligibility not confirmed
- Contract
- Not mentioned in the advert
- Experience asked for
- Not mentioned in the advert
- Pay
- Not mentioned in the advert
Remote flexibility
Region Restricted
Remote work is allowed, but the listing limits candidates to Remote (world).
What the employer says
- Source listing states candidate location: "Remote (world)"
What Nomaders makes of it
- Nomaders could not match this to a wider region
- Check the original posting
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
Before you apply
Questions worth asking: Nomaders interpretation
- The advert does not say where you can be based. Ask which countries they can legally employ or contract you from.
- No pay is stated. Ask for the salary range before investing time in interviews.
- The advert does not say whether this is employment or a contractor arrangement. Ask, as it affects tax and benefits.
Produced automatically from this advert's text; not reviewed by a person. The employer's own page is the final word.
About the role
Role Overview
We are seeking an AI Researcher with deep experience in inference optimization to design, evaluate, and deploy high-performance inference systems for large-scale machine learning models. You will work at the intersection of model architecture, systems engineering, and hardware-aware optimization , improving latency, throughput, and cost efficiency across real-world production environments.
Key Responsibilities
Research and develop techniques to optimize inference performance for large neural networks.
Improve latency, throughput, memory efficiency, and cost per inference .
Design and evaluate model-level optimizations (quantization, pruning, KV-cache optimization, architecture-aware simplifications).
Implement systems-level optimizations (dynamic batching, kernel fusion, multi-GPU inference, prefill vs decode optimization).
Benchmark inference workloads across hardware accelerators.
Collaborate with engineering teams to deploy optimized inference pipelines .
Translate research insights into production-ready improvements .
Required Qualifications
Strong background in machine learning, deep learning, or AI systems .
Hands-on experience optimizing inference for large-scale models .
Proficiency in Python and modern ML frameworks (e.g., PyTorch).
Experience with inference tooling (e.g., Triton, TensorRT, vLLM, ONNX Runtime).
Ability to design experiments and communicate results clearly.
Preferred / Nice-to-Have Qualifications
Experience deploying production inference systems at scale .
Familiarity with distributed and multi-GPU inference .
Experience contributing to open-source ML or inference frameworks .
Authorship or co-authorship of peer-reviewed research papers in machine learning, systems, or related fields.
Experience working close to hardware (CUDA, ROCm, profiling tools).
What Success Looks Like
Measurable gains in latency, throughput, and cost efficiency .
Requirements
- ·Strong background in machine learning, deep learning, or AI systems .
- ·Hands-on experience optimizing inference for large-scale models .
- ·Proficiency in Python and modern ML frameworks (e.g., PyTorch).
- ·Experience with inference tooling (e.g., Triton, TensorRT, vLLM, ONNX Runtime).
- ·Ability to design experiments and communicate results clearly.
Benefits
No benefits package published with this listing. Ask about it at first interview.
How to apply
- 1Check the flexibility label above, region restricted, matches where you plan to live and work.
- 2Tailor your CV to the role at Featherless AI, mentioning your remote working experience.
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 1mo ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
Pay not stated · You'll be taken to the employer's careers page.