Senior Machine Learning Engineer (Generative AI)

Location: United States - Remote; participation in an in-person orientation process is required.

US base salary: $162,000–$258,000 per year; additional incentive programs may apply.

Company

hirify.global provides a cloud platform combining digital, core, analytics, and AI capabilities for property and casualty insurers worldwide.

What you will do

• Lead the design, implementation, and evolution of GenAI and LLM products, including data ingestion, feature pipelines, model training, fine-tuning, deployment, and monitoring on AWS.
• Architect ML and LLM pipelines for claim summarization, underwriting assistance, pricing and rating intelligence, and developer productivity tools.
• Develop reliable and high-performing LLM solutions using prompt engineering, retrieval-augmented generation, vector databases, and fine-tuning.
• Establish MLOps practices for CI/CD, experimentation, evaluation, observability, responsible AI, security, and production readiness.
• Align GenAI capabilities with the product roadmap and customer adoption goals, including Claims Summary, Underwriting Assistant, Codelift, and other GenAI initiatives.
• Mentor engineers and data scientists, lead design and code reviews, and collaborate with Product Strategy, Professional Services, Security, Finance, BizTech, and GTM teams.

Requirements

• 5+ years of professional experience in Machine Learning and/or Data Science, including end-to-end delivery of production ML systems.
• Must have hirify.global experience.
• Deep expertise in Python and experience building scalable ML/LLM services and pipelines, ideally on AWS with S3, EC2, RDS, and SageMaker.
• Strong understanding of MLOps for model development, deployment, monitoring, lifecycle management, CI/CD for ML, experiment tracking, model registries, and drift detection.
• Hands-on experience with classical and gradient-boosting models, including GLM, Random Forest, and XGBoost, applied to real-world business problems.
• Deep understanding of neural networks and transformer-based architectures for LLMs and chat models, including open-source foundation models, fine-tuning, and inference.
• Experience with prompt engineering, RAG, related LLM architecture patterns, and vector databases for semantic search and retrieval.
• Knowledge of evaluating and monitoring LLM performance with NLP and LLM-assisted metrics, focusing on safety, robustness, and user experience.
• Demonstrated technical leadership in design decisions, complex engineering efforts, mentoring, and code and architecture reviews.

Nice to have

• Bachelor’s or Master’s degree in Computer Science, or equivalent practical experience.
• Experience building data pipelines and features with SQL, Spark, or AWS Glue.
• Experience with Docker, Kubernetes, and backend APIs for exposing ML/LLM services.
• Familiarity with CI/CD, infrastructure as code, TeamCity, and Terraform.
• Background in insurance, banking, or financial services, or interest in developing deep expertise in P&C insurance.

Culture & Benefits

• Flexible work environment with a collaborative, hands-on culture focused on experimentation, learning, and production-grade AI.
• Health, dental, and vision insurance, paid time off, volunteer time off, and a company-sponsored retirement plan.
• Market-competitive pay, incentive programs, and potential bonus, commission, or long-term incentive awards depending on the role.
• Continual development and internal career growth opportunities.
• In-person orientation to support connection, collaboration, and understanding of the company mission.