Applied ML Engineer
4 weeks ago
Are you looking to work on AI technology that's cutting-edge, infused into a user-facing product like never before?
Look no further.
Join Rabbit, a pioneering company developing a first-of-it's-kind AI-powered conversational device. It features a ground-breaking foundation model (Large Action Model) and an operating system powered by natural language. The conversational AI operating system (rabbitOS) breaks away from the limitations of current app-based operating systems.
They are on the verge of something revolutionary, and they want you to be a part of it. We are hiring candidates with a minimum of 2 years' experience, extending to senior/staff levels.
Your role:
As an Applied ML Engineer, you will tackle diverse technical challenges as they scale their ML function. You will need extensive experience working with various ML models, both off-the-shelf packages and open-source solutions, fine-tuning them to address a variety of challenges. You will also work on ML infrastructure supporting various services (LLMs, NLU, Computer Vision, Speech recognition, Speech Synthesis), performance/latency optimization, data services, and more.
This role emphasizes production work, including ML infrastructure setup, deployments, fine-tuning models, building data pipelines, and writing low-level code to address latency challenges.
Skills needed:
• Proven ML Engineering or ML infra/ops experience. A minimum of two years of commercial experience.
• Strong software engineering in Python, C++, with comfort in languages like Go, or Rust, or JS/Typescript
• PyTorch or Tensorflow. TensorRT and ONNX are useful.
• Using models/APIs such as Huggingface, OpenAI, etc. You'll be familiar with fine-tuning those models in areas such as: NLG, NLP, NLU, ASR, TTS, Computer Vision.
• Experience with AI lifecycle frameworks (AWS Sagemaker, Vertex AI, Azure ML, ClearML)
• Solving latency, performance, and inference challenges (grafana, DataDog, etc)
As we're hiring for many roles, we'd also consider those who have a strong background in Back End Engineering (Software Engineering, Infrastructure, DevOps) who have recently entered into Machine Learning.
Nice to have skills:
• Experience with ML-based and real-time customer-facing systems, including distributed systems
• Conversational AI or Voice AI experience
• Experience with on-device Machine Learning (on-device speech, smart speakers, on-device video platforms, etc)
• Websockets, WebRTC
• RAG
• Containers - Kubernetes, Docker
What's on offer:
Rabbit is a well-funded company ($30+ million) with successful start-up co-founders. You'll be part of an exceptional and fast-growing team.
The position is based in Los Angeles, hybrid with 3 days a week on-site in Santa Monica. If you are based in the US but not in LA, relocation support is available. Visas can also be supported.
Compensation:
Estimated salary between $170k-$250k (negotiable), generous shares, Healthcare, Unlimited PTO, Annual comp reviews, and company performance-related bonus.
Interview process:
1 - Initial call with recruiter (Marc at Techire AI) - 30 mins
2 - Call with Head of Applied ML Engineering - 30 mins
3 - Live Coding interview - 45 mins
4 - Final interview - 45 mins
Offer
We estimate the full process will take around 2 weeks. We can move fast if you have availability.
How to apply:
Apply now, via this advert, to Marc Powell at Techire AI for immediate consideration.
Please note Techire AI is a retained staffing partner of Rabbit Inc. and is managing all applications for the Applied ML team. All applications must go through Techire AI to be considered.
We do not accept submissions from other recruitment agencies, consultancies, or outsourcing companies.
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