AI/ML Engineer
Core
Design, build, and deploy machine learning and agentic AI systems that power real-world products, including multi-step reasoning pipelines and connected agent architectures.
Role type
ML/AI Engineer (agentic systems & production deployment)
Builds
Production ML models and agentic AI frameworks for connected applications
Domain
Media, advertising technology, and marketing analytics
Deliverable
production ML models
Required skills
Python, ML fundamentals (Pandas, Scikit-learn, XGBoost), model deployment, Generative AI concepts (LLMs, prompt engineering, RAG, agentic frameworks), Docker, cloud infrastructure (GCP/AWS)
Preferred skills
MLOps/CI-CD, Databricks/Apache Spark, Kubernetes, experiment tracking (MLflow/W&B), recommender systems, neural network development (PyTorch, TensorFlow, JAX)
Technologies
Python, Pandas, Scikit-learn, XGBoost, LangChain, LangGraph, Docker, GCP, AWS, Vertex AI, SageMaker, Cloud Run, EC2, Databricks, Apache Spark, Kubernetes, MLflow, Weights & Biases, PyTorch, TensorFlow, JAX
Responsibilities
End-to-end model development and deployment for production use cases; Building, tuning, and evaluating agentic AI frameworks; Maintaining cloud-based ML infrastructure; Writing clean, well-tested Python code and contributing to shared libraries; Collaborating with product, data engineering, and analytics teams to translate business problems into ML solutions
Seniority
Mid-level (2-5 years experience)