Machine Learning Engineer (AI/NLP)

Location: Seattle, Washington, United States; onsite five days per week

Annual base salary: $125,000–$180,000, plus a target annual bonus of 10%

Company

hirify.global, a Morningstar company, provides a data platform focused on financial and investment insights.

What you will do

• Build and deploy AI/ML capabilities that generate insights from structured and unstructured data, including reports, news, and other textual content.
• Design, train, optimize, monitor, and maintain production-grade models and services for NLP, summarization, semantic search, classification, and prediction.
• Develop solutions using classifiers, transformers, LLMs, and other NLP techniques, integrating them into scalable AI/ML infrastructure.
• Collaborate with engineering, product management, data science, and data collection teams to align models with product and business goals.
• Evaluate emerging GenAI, NLP, and search technologies and translate research findings into practical platform capabilities.
• Contribute to model transparency, evaluation, monitoring, security, data integrity, responsible AI, technical reviews, and team knowledge sharing.

Requirements

• Bachelor’s degree in Computer Science, Mathematics, Data Science, or a related field.
• At least 2 years of software engineering or machine learning engineering experience focused on AI/ML applications.
• Must be authorized to work in the United States without visa sponsorship now or in the future.
• Hands-on expertise with NLP, machine learning, classifiers, transformer models, and large language models.
• Strong programming skills in Python and SQL, with experience using ML and data science libraries such as scikit-learn, pandas, NumPy, TensorFlow, and PyTorch.
• Experience with production systems, scalable data pipelines, distributed systems, cloud-native development, Docker, and Kubernetes.

Nice to have

• Experience with LangChain, LangSmith, and LangGraph in production environments.
• Experience with Apache Kafka, Airflow, Snowflake, Java, or Scala.
• Prior fintech or financial data platform experience.
• Research papers published at AI/ML conferences such as NeurIPS, ICML, or ACL.

Culture & Benefits

• In-person collaboration in a standard office environment.
• Comprehensive health, dental, disability, life insurance, and wellness benefits.
• Paid sabbatical after four years, family and paternity leave, vacation, sick, and volunteer days.
• Annual educational stipend, tuition reimbursement, CFA exam stipend, and training programs.
• 401(k) match, employee stock program, transportation stipend, emergency childcare, and employee assistance resources.
• Employee resource groups, company events, referral bonuses, and quarterly team-building events.