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Senior Machine Learning Engineer

1 month, 1 week ago
United States
Full-time
Senior
Machine Learning Engineer
Software Development
LLM Python PyTorch Vertex AI
Apply Now
Rubrik

Rubrik

Rubrik provides cutting-edge data security and protection solutions, including Zero Trust Data Protection and ransomware recovery, to ensure data readiness and business resilience.

IT Services
1K-5K
Founded 2014
$553M raised
View All Jobs 33

Description

  • Own the full lifecycle of production small language models and classifiers, from base-model selection and training through deployment and iteration.
  • Train, fine-tune, distill, and optimize models using supervised fine-tuning, preference optimization, adversarial training, and post-training techniques.
  • Build real-time and batch inference infrastructure for low-latency enforcement, offline scoring, back-testing, and corpus mining.
  • Optimize serving performance using GPU pooling, KV-cache-aware routing, continuous batching, quantization, and speculative decoding.
  • Design and maintain canary, shadow, and A/B traffic workflows to validate model changes on live customer traffic.
  • Build synthetic data pipelines, policy back-testing systems, and online/offline evaluation frameworks that detect regressions and quality issues.
  • Mine production signals, customer feedback, and agent-session insights to improve policies, reduce false positives, and surface security gaps.
  • Diagnose model failures across data, training, architecture, and serving layers and implement the correct fix in the right layer.
  • Partner with product, customer-facing, security, and platform teams to translate governance needs into modeling work and integrate models safely into production.
  • Provide technical leadership on a pillar of the model stack and mentor engineers working on applied ML systems.

Requirements

  • Bachelor's degree or higher in Computer Science, Machine Learning, Computer Engineering, Statistics, or a closely related technical field.
  • 2+ years of professional ML experience with end-to-end ownership of models in production.
  • Proficiency in Python and PyTorch, or equivalent tools, for training and evaluation.
  • Hands-on experience training, fine-tuning, or distilling language models or classifiers in production.
  • Experience with supervised fine-tuning and at least one preference-optimization method such as DPO, RLAIF, or RLHF.
  • Production experience with serving frameworks such as vLLM, SGLang, TensorRT-LLM, or equivalent.
  • Experience optimizing inference with continuous batching, KV-cache strategies, and inference-time quantization.
  • Experience designing closed-loop ML systems that connect evaluation, telemetry, data curation, and synthetic data back into training.
  • Comfort operating at production scale in high-QPS, safety-critical request paths with customer-visible consequences.
  • Preferred: deep background in AI safety and red-teaming, including adversarial ML and prompt-injection defense.
  • Preferred: expertise in evaluation methodology such as LLM-as-judge pipelines, calibration monitoring, and adversarial benchmarks.
  • Preferred: experience with context-fusion and retrieval systems that combine sensitivity, identity, and behavioral history.
  • Preferred: production experience with low-latency inference for streaming or safety-critical systems.
  • Preferred: knowledge of label-efficient training methods such as weak supervision, active learning, and embedding-based retrieval.
  • Preferred: hands-on knowledge distillation experience transferring frontier model capabilities to smaller production models.
  • Preferred: familiarity with tool-use frameworks, model gateway architectures such as MCP or LiteLLM, and autonomous agent patterns.
  • Preferred: active open-source contributions to mainstream ML training, serving, or evaluation libraries.

Benefits

  • US base salary range of $188,500 to $282,700.
  • Role is eligible for bonus potential.
  • Role is eligible for equity.
  • Role includes benefits.
  • Equal opportunity employer with accommodations available for qualified individuals with disabilities.

Interested in this position?

Apply directly on the company website

Apply Now

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