{"schemaVersion":"jobsearcher.job.v1","id":"ef35a4140fefe8543ece2e8a","url":"https://jobsearcher.com/jobs/ef35a4140fefe8543ece2e8a","canonicalUrl":"https://jobsearcher.com/jobs/ef35a4140fefe8543ece2e8a","title":"AI Machine Learning Engineer (AI / ML: Python / Go)","description":"About Benzinga\nBenzinga is a fast-growing financial media and data technology company reshaping how investors access information. We combine artificial intelligence, machine learning, and real-time data pipelines to surface insights before they hit the mainstream. Our platforms deliver structured news, sentiment analytics, and financial data APIs used by leading banks, fintechs, and AI companies worldwide.\nWe're seeking a highly motivated AI / Machine Learning Engineer who thrives at the intersection of data science and backend engineering — someone who can take a model from notebook to production, and architect intelligent systems in Go and Python that scale to millions of requests.\nThe ideal candidate is a self-starter who independently identifies opportunities, experiments with new approaches, and ships production-ready solutions without constant direction.\n________________________________________\nKey Responsibilities\nAI / Machine Learning\nResearch, design, and deploy machine learning models across NLP, time-series forecasting, and event detection domains.\nBuild LLM-driven systems (e.g. summarization, RAG pipelines, embedding search) optimized for financial news and quantitative data.\nDevelop model serving APIs and scalable inference layers using Go or Python.\nImplement model monitoring, drift detection, and continuous retraining pipelines.\nWork with financial text (earnings call transcripts, filings, news) to extract structured insights.\nCollaborate with data engineers to build training datasets, feature stores, and embedding databases.\nBackend & Infrastructure\nDevelop and maintain high-performance Python or Go microservices that integrate with AI systems and Go data APIs.\nDesign and optimize real-time inference pipelines on AWS, leveraging ECS/EKS, S3, and Lambda.\nEnsure low-latency, fault-tolerant, and scalable delivery of AI-powered data.\nImplement CI/CD for ML workflows, including containerization, automated deployment, and versioning.\nPartner with DevOps to manage cloud infrastructure and ensure robust observability for AI workloads.\nRequirement for applying:\nDuring your screening you will be required to submit a Loom video walkthrough of your most exceptional product, share relevant code/repo links, and describe the biggest challenge you faced building it.\nRequired Qualification\n4+ years of experience in AI/ML or data engineering roles, with a proven track record of deploying ML models in production.\nComputer science degree (Bachelor minimum)\nDeep proficiency in Python (data, ML) and Go (backend, microservices).\nHands-on experience with ML frameworks such as PyTorch, TensorFlow, or Hugging Face.\nExperience with transformer architectures, embeddings, or fine-tuning LLMs.\nStrong understanding of data pipelines, feature extraction, and model lifecycle management.\nFamiliarity with Docker, Kubernetes, and AWS (EKS, S3, Lambda, EC2).\nExcellent problem-solving skills and ability to work independently in a distributed environment.\nPreferred Skills / Experience\nStartup experience.\nFinancial services or fintech background\nExperience building LLM-powered APIs or retrieval-augmented generation (RAG) systems.\nKnowledge of vector databases (e.g., Pinecone, Weaviate, FAISS, OpenSearch kNN).\nExperience with Kafka, LangChain, or data streaming architectures.\nFamiliarity with financial data systems, real-time analytics, or news NLP.\nExposure to MLOps tools (MLflow, BentoML, SageMaker, Airflow, etc.).\nContributions to open-source ML or Go projects are a strong plus.\nTech Stack\nLanguages: Python, Go\nML Frameworks: PyTorch, TensorFlow, Hugging Face, LangChain\nCloud: AWS (EKS, ECS, S3, Lambda, EC2, IAM)\nContainers & Orchestration: Docker, Kubernetes\nData & Streaming: Kafka, Postgres, OpenSearch\nCI/CD: GitHub Actions, GitLab CI\nMonitoring: Datadog, Prometheus, Grafana\nVersion Control: Git (Gitlab / Github)\n________________________________________\nWhy Join Benzinga\nBuild and ship production AI systems that shape how financial markets understand information.\nOperate with full creative freedom — explore, experiment, and execute your ideas end-to-end.\nWork with a lean, highly technical team where initiative and ownership are celebrated.\nFully remote, high-trust environment that rewards curiosity, speed, and execution.","company":"Benzinga","rawCompany":"benzinga","city":"Remote","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-08-05T00:13:46.609Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"AI Machine Learning Engineer (AI / ML: Python / Go)","description":"About Benzinga\nBenzinga is a fast-growing financial media and data technology company reshaping how investors access information. We combine artificial intelligence, machine learning, and real-time data pipelines to surface insights before they hit the mainstream. Our platforms deliver structured news, sentiment analytics, and financial data APIs used by leading banks, fintechs, and AI companies worldwide.\nWe're seeking a highly motivated AI / Machine Learning Engineer who thrives at the intersection of data science and backend engineering — someone who can take a model from notebook to production, and architect intelligent systems in Go and Python that scale to millions of requests.\nThe ideal candidate is a self-starter who independently identifies opportunities, experiments with new approaches, and ships production-ready solutions without constant direction.\n________________________________________\nKey Responsibilities\nAI / Machine Learning\nResearch, design, and deploy machine learning models across NLP, time-series forecasting, and event detection domains.\nBuild LLM-driven systems (e.g. summarization, RAG pipelines, embedding search) optimized for financial news and quantitative data.\nDevelop model serving APIs and scalable inference layers using Go or Python.\nImplement model monitoring, drift detection, and continuous retraining pipelines.\nWork with financial text (earnings call transcripts, filings, news) to extract structured insights.\nCollaborate with data engineers to build training datasets, feature stores, and embedding databases.\nBackend & Infrastructure\nDevelop and maintain high-performance Python or Go microservices that integrate with AI systems and Go data APIs.\nDesign and optimize real-time inference pipelines on AWS, leveraging ECS/EKS, S3, and Lambda.\nEnsure low-latency, fault-tolerant, and scalable delivery of AI-powered data.\nImplement CI/CD for ML workflows, including containerization, automated deployment, and versioning.\nPartner with DevOps to manage cloud infrastructure and ensure robust observability for AI workloads.\nRequirement for applying:\nDuring your screening you will be required to submit a Loom video walkthrough of your most exceptional product, share relevant code/repo links, and describe the biggest challenge you faced building it.\nRequired Qualification\n4+ years of experience in AI/ML or data engineering roles, with a proven track record of deploying ML models in production.\nComputer science degree (Bachelor minimum)\nDeep proficiency in Python (data, ML) and Go (backend, microservices).\nHands-on experience with ML frameworks such as PyTorch, TensorFlow, or Hugging Face.\nExperience with transformer architectures, embeddings, or fine-tuning LLMs.\nStrong understanding of data pipelines, feature extraction, and model lifecycle management.\nFamiliarity with Docker, Kubernetes, and AWS (EKS, S3, Lambda, EC2).\nExcellent problem-solving skills and ability to work independently in a distributed environment.\nPreferred Skills / Experience\nStartup experience.\nFinancial services or fintech background\nExperience building LLM-powered APIs or retrieval-augmented generation (RAG) systems.\nKnowledge of vector databases (e.g., Pinecone, Weaviate, FAISS, OpenSearch kNN).\nExperience with Kafka, LangChain, or data streaming architectures.\nFamiliarity with financial data systems, real-time analytics, or news NLP.\nExposure to MLOps tools (MLflow, BentoML, SageMaker, Airflow, etc.).\nContributions to open-source ML or Go projects are a strong plus.\nTech Stack\nLanguages: Python, Go\nML Frameworks: PyTorch, TensorFlow, Hugging Face, LangChain\nCloud: AWS (EKS, ECS, S3, Lambda, EC2, IAM)\nContainers & Orchestration: Docker, Kubernetes\nData & Streaming: Kafka, Postgres, OpenSearch\nCI/CD: GitHub Actions, GitLab CI\nMonitoring: Datadog, Prometheus, Grafana\nVersion Control: Git (Gitlab / Github)\n________________________________________\nWhy Join Benzinga\nBuild and ship production AI systems that shape how financial markets understand information.\nOperate with full creative freedom — explore, experiment, and execute your ideas end-to-end.\nWork with a lean, highly technical team where initiative and ownership are celebrated.\nFully remote, high-trust environment that rewards curiosity, speed, and execution.","datePosted":"2026-08-05T00:13:46.609Z","dateModified":"2026-08-05T00:13:46.609Z","hiringOrganization":{"@type":"Organization","name":"Benzinga","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"ef35a4140fefe8543ece2e8a"},"url":"https://jobsearcher.com/jobs/ef35a4140fefe8543ece2e8a"}}