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BenzingaPosted 1 month ago

AI Machine Learning Engineer (AI / ML: Python / Go)

RemoteUnited States

Full TimeSmall

Job Summary

Research, design, and deploy machine learning models across NLP, time-series forecasting, and event detection domains. Build LLM-driven systems optimized for financial news and quantitative data, including summarization, RAG pipelines, and embedding search. Develop model serving APIs and scalable inference layers using Go or Python, while implementing monitoring, drift detection, and continuous retraining pipelines. Collaborate with data engineers to build training datasets, feature stores, and embedding databases. Design and optimize real-time inference pipelines on AWS, ensuring low-latency, fault-tolerant delivery of AI-powered data. Implement CI/CD for ML workflows, including containerization, automated deployment, and versioning. Partner with DevOps to manage cloud infrastructure and ensure robust observability for AI workloads.

Required Qualifications

  • 4+ years of experience in AI/ML or data engineering roles, with a proven track record of deploying ML models in production
  • Computer science degree (Bachelor minimum)
  • Deep proficiency in Python (data, ML) and Go (backend, microservices)
  • Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or Hugging Face
  • Experience with transformer architectures, embeddings, or fine-tuning LLMs
  • Strong understanding of data pipelines, feature extraction, and model lifecycle management
  • Familiarity with Docker, Kubernetes, and AWS (EKS, S3, Lambda, EC2)
  • Excellent problem-solving skills and ability to work independently in a distributed environment

Desired Qualifications

  • Startup experience
  • Financial services or fintech background
  • Experience building LLM-powered APIs or retrieval-augmented generation (RAG) systems
  • Knowledge of vector databases (e.g., Pinecone, Weaviate, FAISS, OpenSearch kNN)
  • Experience with Kafka, LangChain, or data streaming architectures
  • Familiarity with financial data systems, real-time analytics, or news NLP
  • Exposure to MLOps tools (MLflow, BentoML, SageMaker, Airflow, etc.)
  • Contributions to open-source ML or Go projects

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