Senior ML Engineer

Join our partner to build the ML systems that power actionable insights for investors everywhere. 
 

What you’ll do

• Design, train, and evaluate ML/DL models (with a strong emphasis on classical ML where appropriate) for ranking, prediction, and risk/quality signals.
• Productionize models end-to-end: data pipelines, feature stores, deployment, scaling, monitoring, and optimization.
• Collaborate with product, research, and engineering to translate financial problems into measurable ML solutions.
• Own experiment design, metrics, and A/B testing; communicate findings clearly to technical and non-technical stakeholders.

• Contribute to model governance, reproducibility, and documentation across the ML lifecycle.

   

What you’ll bring

• MS or PhD in Computer Science, Data Science, AI, or a related quantitative field.
• 4+ years building and shipping ML/DL models in production (with depth in classical ML methods).
• Expert coding in Python; hands-on with PyTorch and/or TensorFlow and common DL libraries.
• Strong foundations in linear algebra, calculus, statistics, and probability.
• Solid grasp of algorithms and data structures.
• Proficiency with Pandas, scikit-learn, and the broader Python data stack.
• Experience with model deployment, optimization, scaling, and serving.
• Excellent problem-solving, analytical, and quantitative skills.
• Hands-on experience delivering solutions in the financial domain.

• Clear, concise communicator and a collaborative team player.

   

Nice to have

• Research or applied experience in LLMs/NLP and modern machine learning.
• Work with multi-modal data (e.g., text, tabular/market data, images, audio).
• Familiarity with AWS or GCP for large-scale training/inference.
• Understanding of MLOps and production ML workflows (CI/CD for models, monitoring, model/data versioning).
• Background in information retrieval, knowledge graphs, or reasoning.