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.