Machine Learning Engineer
Core
Building high-performance, scalable ML systems including classical models, LLMs, and multiagent architectures to translate AI-driven ideas into real-world applications.
Role type
Senior IC machine learning engineer (LLMs & agents)
Builds
Production-grade ML pipelines, LLM-based solutions, and agent-based architectures
Domain
Generative AI, Large Language Models, Multi-agent systems
Deliverable
production ML models
Required skills
LLM solution development, Python, PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers, agent architecture, prompt engineering, LLM guardrails, CI/CD, cloud platforms (AWS/GCP/Azure), container technologies (Docker/Kubernetes)
Preferred skills
Vector databases (Pinecone/Weaviate/FAISS), orchestration tools (MLflow/Airflow)
Technologies
PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers, AWS, GCP, Azure, Docker, Kubernetes, Pinecone, Weaviate, FAISS, MLflow, Airflow
Responsibilities
Designing and implementing machine learning pipelines and models including LLM-based solutions, Translating prototypes and research into production-grade code, Developing and finetuning foundation models and LLMs for specific use cases, Training and optimizing numeric machine learning models, Applying prompt engineering and building agent-based architectures, Integrating models into backend systems and supporting real-time batch inference services, Ensuring safe and robust use of generative AI through guardrails and observability tools
Seniority
Senior, hands-on IC