Senior Machine Learning Engineer
Location: New York, NY (Or Boston, MA)
About the Company
We're a leading financial services startup revolutionizing a specific untapped vertical. We have incredible product market fit and backing. Our teams leverage cutting-edge ML and AI to build predictive models, automate workflows and unlock new revenue opportunities.
What You'll Do
- Design, implement and maintain end-to-end ML pipelines: data ingestion, feature engineering, model training, evaluation and deployment
- Develop and productionize quantitative models for pricing, risk forecasting, alpha generation and other finance-focused use cases
- Integrate and fine-tune large language models (LLMs) for document analysis, report generation and conversational interfaces
- Translate business needs into scalable, high-performance solutions
- Monitor model performance in production, troubleshoot issues and iterate to improve accuracy, latency and robustness
What You Bring
- 5+ years of hands-on experience in applied science / ML engineering, with a track record of shipping production models in finance, fintech, or insurance tech.
- Strong proficiency in Python, ML libraries (scikit-learn, PyTorch, TensorFlow) and MLOps tools (Docker, Kubernetes, Airflow, MLflow, etc.)
- Demonstrated experience building predictive models for financial time series, credit/risk scoring or algorithmic strategies
- Practical expertise with LLMs: prompt engineering, fine-tuning and deployment (e.g., Hugging Face Transformers, OpenAI API)
- Solid software engineering skills: clean code, testing, CI/CD and version control
- Self-starter who can own projects end-to-end, from ideation and prototyping through to deployment and maintenance
- Excellent communication skills and ability to work cross-functionally in a fast-paced environment
- Experience at (or a very strong desire to join) an early-stage startup
Nice to Have
- Master's or PhD in CS, Statistics, Applied Math, Financial Engineering or related field
- Experience with cloud platforms (AWS, GCP or Azure) and distributed computing
- Background in algo-trading, portfolio optimization or high-frequency data analysis
If you're passionate about applying ML at scale in finance and thrive working independently on end-to-end solutions, we'd love to hear from you. Please apply with your resume and a brief note on your most relevant project.