Note: The job is a remote job and is open to candidates in USA. Benzinga is a fast-growing financial media and data technology company reshaping how investors access information. They are seeking a highly motivated AI / Machine Learning Engineer who thrives at the intersection of data science and backend engineering, responsible for deploying machine learning models and architecting intelligent systems.
Responsibilities
- Research, design, and deploy machine learning models across NLP, time-series forecasting, and event detection domains
- Build LLM-driven systems (e.g. summarization, RAG pipelines, embedding search) optimized for financial news and quantitative data
- Develop model serving APIs and scalable inference layers using Go or Python
- Implement model monitoring, drift detection, and continuous retraining pipelines
- Work with financial text (earnings call transcripts, filings, news) to extract structured insights
- Collaborate with data engineers to build training datasets, feature stores, and embedding databases
- Develop and maintain high-performance Python or Go microservices that integrate with AI systems and Go data APIs
- Design and optimize real-time inference pipelines on AWS, leveraging ECS/EKS, S3, and Lambda
- Ensure low-latency, fault-tolerant, and scalable 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
Skills
- 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
- 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 are a strong plus
Benefits
- Build and ship production AI systems that shape how financial markets understand information.
- Operate with full creative freedom — explore, experiment, and execute your ideas end-to-end.
- Work with a lean, highly technical team where initiative and ownership are celebrated.
- Fully remote, high-trust environment that rewards curiosity, speed, and execution.
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