AI ML Engineer
Skills
- Production-ready Python development
- MLOps experience (CI/CD, continuous training, evaluation, MLflow)
- Model development with PyTorch and/or TensorFlow
- Generative AI techniques (RAG, agentic systems, prompt engineering)
- Experience with cloud platforms (GCP preferred) and containerization (Docker, Kubernetes)
- API development (FastAPI, Flask or similar)
- Big data systems (Databricks, BigQuery or equivalent) and strong SQL skills
- Model evaluation, monitoring, and optimization for production
Responsibilities
- Design and architect AI/ML solutions to extract insights from unstructured banking documents (parsers and classifiers).
- Develop, deploy, and maintain production ML models and services, writing clean, testable, maintainable code.
- Establish evaluation criteria and monitoring for model performance, tradeoffs across speed, accuracy, and cost.
- Implement MLOps and DevOps practices including CI/CD, continuous training, evaluation, and performance tracking.
- Collaborate daily with product managers, domain experts, engineers, and designers to ship features.
- Stay current with ML best practices and open-source frameworks; propose and implement improvements.
Education
- Bachelor's degree in Computer Science, Engineering, Data Science, or related field (or equivalent experience)
- Advanced degree (MS/PhD) in relevant field preferred but not required
- Relevant coursework or certifications in machine learning, NLP, or data engineering
Benefits
- Unlimited PTO
- $1,000 learning & development fund
- Remote-first work environment
- Comprehensive medical, dental, and vision benefits
- 401(k) retirement plan
- Free Equinox membership or $1,650 annual fitness fund
- Paid parental leave (12 weeks primary, 4 weeks secondary)
Average salary estimate
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