Deskripsi Pekerjaan
At Nexus Intelligence, we are architecting the next generation of enterprise Generative AI. We don't just fine-tune models; we build foundational intelligence that powers decision-making for Fortune 500 companies. We are looking for a Senior Machine Learning Engineer who thrives at the intersection of cutting-edge research and robust, scalable production systems.
You will join a elite, high-autonomy team of researchers and engineers spinning up custom LLMs, RAG architectures, and agentic workflows. This is a greenfield opportunity to define the technical strategy for our core AI platform, working directly with the CTO and founding team. If you want to move fast, own significant surface area, and see your code impact millions of users immediately, this is your role.
Why Nexus?
- Compute Freedom: Unlimited access to H100/A100 clusters via our strategic cloud partnerships.
- Research-to-Production Pipeline: Publish at top-tier venues (NeurIPS, ICML, ICLR) while shipping to prod weekly.
- Equity Upside: Pre-IPO stock options with a 4-year vest, 1-year cliff, and accelerated vesting on change of control.
- Culture: Zero bureaucracy, written async-first communication, quarterly offsites (Japan, Portugal, Utah).
Tanggung Jawab
- Design, train, and deploy Large Language Models (LLMs) and multimodal architectures for high-stakes enterprise use cases.
- Own the full MLOps lifecycle: data curation, distributed training (FSDP/DeepSpeed), evaluation frameworks, quantization, and low-latency serving (vLLM/TensorRT-LLM).
- Architect and optimize Retrieval-Augmented Generation (RAG) pipelines and Agentic workflows (LangGraph, custom tool use) for reliability and hallucination reduction.
- Collaborate with Product and Research to translate ambiguous business problems into measurable ML objectives and evaluation benchmarks.
- Establish best practices for model monitoring, drift detection, guardrails, and automated retraining loops in production.
- Mentor junior engineers and conduct rigorous code/design reviews focusing on scalability, reproducibility, and security.
- Contribute to open-source tooling and publish findings at industry conferences to build Nexus's technical brand.
Kualifikasi
- Education: MS/PhD in Computer Science, Machine Learning, Statistics, or equivalent practical experience.
- Experience: 5+ years professional ML engineering experience; 2+ years specifically deploying LLMs/Generative AI in production environments.
- Frameworks: Expert-level proficiency in PyTorch, JAX, or TensorFlow; deep hands-on experience with Hugging Face ecosystem (Transformers, Accelerate, PEFT, TRL).
- Distributed Systems: Proven track record training/fine-tuning models >7B parameters on multi-node GPU clusters (FSDP, DeepSpeed, Megatron-LM).
- Serving & Optimization: Expertise in inference optimization: Quantization (GPTQ, AWQ, bitsandbytes), Speculative Decoding, KV Cache management, Triton/vLLM/TensorRT-LLM.
- Data & Eval: Strong opinions on data quality, synthetic data generation, and building rigorous evaluation suites (beyond vibe checks) for open-ended generation.
- Engineering Rigor: Production-grade Python (type hints, testing, CI/CD), Docker/Kubernetes, and Infrastructure-as-Code (Terraform/Pulumi).