AI/ML Engineer – Python & Go

About the role

Benzinga is looking for an AI/ML Engineer who can bridge data science and backend development. You will take machine‑learning models from research notebooks to production‑grade services, building scalable AI systems in Python and Go that serve millions of financial data requests.

Key responsibilities

• Research, design, and deploy ML models for NLP, time‑series forecasting, and event detection on financial text.
• Build LLM‑driven pipelines (summarization, RAG, embedding search) optimized for news and quantitative data.
• Develop and maintain model serving APIs and inference layers using Python or Go.
• Implement model monitoring, drift detection, and continuous retraining pipelines.
• Collaborate with data engineers to create training datasets, feature stores, and embedding databases.
• Design high‑performance microservices that integrate AI components with Go data APIs.
• Optimize real‑time inference pipelines on AWS (ECS/EKS, S3, Lambda) for low‑latency, fault‑tolerant delivery.
• Set up CI/CD for ML workflows, including containerization, automated deployment, and versioning.

Required profile

• 4+ years of experience in AI/ML or data engineering, with production model deployments.
• Bachelor’s degree in Computer Science or related field (minimum).
• Strong proficiency in Python (data/ML) and Go (backend microservices).
• Hands‑on experience with PyTorch, TensorFlow or Hugging Face libraries.
• Experience with transformer architectures, embeddings, and fine‑tuning LLMs.
• Deep understanding of data pipelines, feature extraction, and model lifecycle management.
• Familiarity with Docker, Kubernetes and AWS services (EKS, ECS, S3, Lambda, EC2).

Required skills

• Python
• Go
• PyTorch
• TensorFlow
• Hugging Face
• Transformer models
• Docker
• Kubernetes
• AWS (EKS, ECS, S3, Lambda, EC2)
• CI/CD pipelines
• Containerization
• Microservices architecture
• Model monitoring & drift detection
• Feature stores & embedding databases