Machine Learning Engineer II developing production ML models for Affirm’s pay - over - time platform. Building credit decisioning systems, scalable pipelines, and algorithms that predict default and guide approvals.
About the role
- Sr. AI/ML Engineer building and deploying AI models for AlertMedia’s risk intelligence and response SaaS platform. Optimizing LLMs, machine-learning pipelines and production AI features.
Responsibilities
- Lead the evaluation, training and integration of advanced AI and machine learning models across the product suite
- Help shape AI strategy by identifying appropriate models for use cases
- Optimize model performance through fine-tuning and prompt engineering
- Train and fine-tune supervised learning models for internal tools and customer-facing features
- Lead prompt engineering and testing efforts for LLM use cases
- Design and implement evaluation pipelines for LLMs and traditional ML models
- Work with and optimize Elasticsearch-backed data systems powering AI and intelligence pipelines
- Identify opportunities to improve AI models, data pipelines and engineering workflows
- Develop tools and frameworks for prompt iteration, model benchmarking and performance tracking
- Coordinate with the security team to ensure AI compliance standards
- Evaluate commercial and open-source LLMs for performance, cost, alignment and reliability
- Collaborate with product and engineering teams to integrate AI features safely, scalably and maintainably
- Monitor, evaluate and continuously improve production AI and ML model performance
- Stay informed about emerging NLP, machine learning and AI infrastructure research
- Contribute to AlertMedia’s culture, values and vision
Requirements
- Bachelor’s degree in a technical field such as computer science, computer engineering or related field preferred
- 2+ years of software engineering experience; Python preferred
- 4–6+ years of experience in data science and/or software engineering, specifically in machine learning engineering or applied AI
- Strong understanding of LLMs and traditional machine learning methods
- Experience with prompt engineering, model fine-tuning and evaluation
- Familiarity with model evaluation best practices, including offline metrics, cross-validation and A/B testing
- Proficiency in Python and ML libraries such as scikit-learn, PyTorch, TensorFlow and Hugging Face
- Experience with Elasticsearch or other large-scale search and indexing platforms
- Experience with cloud-based ML tooling such as SageMaker and Bedrock and data workflows
- Demonstrated experience training and deploying supervised learning models, ideally in production environments
- Ability to work independently and collaboratively on cross-functional teams
- Strong organizational skills and ability to manage multiple projects in parallel
- Ability and desire to work in a fast-paced, challenging environment
- Must have existing authorization to work in Canada without sponsorship now or in the future
- Finalists may be asked to complete identity verification and present valid government-issued identification
Benefits
- Competitive base salary
- Company-wide bonus program
- Generous and flexible time off and parental leave policies
- Medical, Dental, Vision and Life Insurance 100% paid for employees
- Rewards and incentives
- Community service opportunities
- Access to downtown Austin office with 360-degree views, building gym and nearby running trails
- Ongoing career development opportunities through the Learning & Development team
- Meaningful work and career growth in a fast-moving, global company with an award-winning culture
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