Machine Learning Engineer

2 weeks ago

Santa Clara, CA, United States Bayone Full time
Job Title: Machine Learning Engineer
Location: San Jose, CA (Hybrid - 3 days onsite)
Duration: 6-12+ Months (Possible Extension or FTE conversion)

About Position:
We are seeking a hands-on Machine Learning Engineer with a strong computer science foundation and practical experience building LLMs. This role is 100% technical and requires an engineer who can design, train, optimize, and deploy LLMs for real-world applications.

Responsibilities
  • Design, train, and fine-tune Cisco-specific LLMs for enterprise use cases.
  • Build robust data pipelines for large-scale text preprocessing and model training.
  • Optimize LLMs for efficiency using techniques such as LoRA, quantization, and distributed training.
  • Deploy and serve models in production environments using modern ML infrastructure.
  • Collaborate with the AI Innovation core team to research, test, and scale new LLM architectures and techniques.
  • Work closely with cross-functional teams to apply models to security assessment and future CX use cases.

Must-Have Qualifications
  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field.
  • Strong programming skills in Python (with C++/Java as a plus).
  • Hands-on experience building and training LLMs (small, medium, or large scale).
  • Deep understanding of transformer architectures, tokenization, embeddings, and pretraining vs. fine-tuning methods.
  • Proficiency with PyTorch (primary) and familiarity with Hugging Face ecosystem.
  • Experience with distributed training frameworks (DeepSpeed, FSDP, DDP, Accelerate, Horovod).
  • Knowledge of model deployment tools (ONNX, TorchScript, Triton Inference Server, FastAPI).

Good-to-Have Skills
  • Familiarity with MLOps workflows (MLflow, Weights & Biases, ClearML).
  • Knowledge of vector databases (FAISS, Pinecone, Weaviate, Milvus) and RAG pipelines.
  • Experience with cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI).
  • Background in security/compliance-aware ML (prompt injection defense, data leakage prevention).
  • Collaboration and communication skills to work with local and global teams.

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