AI Machine Learning Engineer – AI, ML, Python, Go

Job Description:

• AI / Machine Learning 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
• Backend & Infrastructure 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

Requirements:

• 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

Benefits:

• Fully remote, high-trust environment that rewards curiosity, speed, and execution
• 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