Member of the Technical Staff — AI/ML
Designs, builds, and deploys production AI/ML systems for financial operations like invoice matching and payment reconciliation. Requires 5+ years software engineering with 2+ years applied AI/ML, expertise in LLMs, RAG, and Python/PyTorch.
About the job
What You’ll Do
- Build & Deploy: Create production-ready AI applications that directly address customer financial workflow challenges.
- Optimize AI Features: Implement and refine capabilities like invoice matching, payment reconciliation, and financial document processing.
- Adapt & Fine-Tune Models: Apply and optimize LLMs, RAG systems, and other AI architectures for specific financial use cases.
- Engineer for Scale: Develop robust AI pipelines from data ingestion through inference, ensuring reliability, scalability, and maintainability.
- Automate Workflows: Design AI-powered automations that reduce manual effort in finance operations.
- Collaborate Cross-Functionally: Partner with Product, Engineering, and customers to translate business needs into effective AI solutions.
- Measure Impact: Create evaluation frameworks to track AI system performance and quantify business outcomes.
You Might Be a Fit If You…
- Have 5+ years of software engineering experience, with at least 2 years focused on applied AI/ML in production environments.
- Have integrated and fine-tuned LLMs for real-world applications.
- Have built retrieval-augmented generation (RAG) systems for document-intensive workflows.
- Understand MLOps best practices, from model deployment pipelines to monitoring and A/B testing.
- Are fluent in Python and experienced with PyTorch, TensorFlow, and Transformers.
- Have shipped AI products that solved real business problems — not just prototypes.
- Have strong experience with data preprocessing and feature engineering for AI.
- Can translate business requirements into clear, impactful technical solutions.
- Have experience integrating AI systems into existing enterprise platforms.
Compensation
Top-of-market salary and equity package
Benefits (for U.S.-based full-time employees)
- Medical, dental & vision insurance coverage for you
- 401(k) & Match
- Equity
- Flexible PTO
- Parental Leave
Skills
Python, PyTorch, TensorFlow, Transformers, LLMs, RAG, MLOps, Data Preprocessing, Feature Engineering
Similar jobs
ML Engineering jobs
Cinder
New York, NY
Build and operate production machine-learning systems for content safety, from messy customer data through classification, evaluation, and inference. The role requires 5+ years of ML engineering experience, strong Python and MLOps skills, and sound judgment across classical models and LLMs.
Perplexity
San Francisco, CA
Build AI agent harnesses, models, and product capabilities that enable agents to perform complex work across digital environments. The role combines applied AI research and software engineering, requiring Python proficiency, strong product judgment, and experience with agent tooling, reinforcement learning, or browser technologies.
Mercor
San Francisco, CA
Builds the platform, verifiers, environments, and grading infrastructure used to evaluate enterprise AI agents at scale. The role combines strong software engineering with expertise in agent runtimes, evaluation design, benchmarks, and production failure analysis.
Applied Intuition
Sunnyvale, CA
Optimizes distributed machine learning training and high-throughput offline inference across large accelerator clusters. The role focuses on profiling, scaling efficiency, cluster goodput, GPU performance, and cost-effective processing of autonomy data.
Firecrawl
San Francisco, CA
Build and operate production machine-learning systems for search ranking, relevance, extraction quality, and LLM-driven features. The role requires production ML ownership, ranking or relevance expertise, large-scale data experience, Python, and rigorous experimentation skills.