Senior Data Engineer building cloud - native data and ML platforms for Hive.co’s event - marketing automation products. Owning pipelines, model infrastructure, and audience - data systems at scale.
About the role
- Senior Machine Learning Engineer on AI Generation Engine team designing and building AI-first products at SandboxAQ. Focus on the end-to-end ML lifecycle from data exploration to model deployment.
Responsibilities
- Design, construct, and manage robust data pipelines for the training, validation, and continuous retraining of Large Quantitative Models (LQMs) and agentic frameworks.
- Develop, implement, and rigorously test novel ML models and algorithms, defining appropriate metrics to ensure model performance aligns with high-level product objectives.
- Contribute to the efforts in cleaning, transforming, and engineering features from complex and large-scale datasets to optimize LQM performance and predictive accuracy.
- Conduct deep analysis of model behavior, performance, and failure modes, tuning hyper-parameters and optimizing model architecture for efficiency, speed, and accuracy in a production context.
- Collaborate closely with AI researchers, product managers, and SWEs to translate high-level business objectives into actionable ML development and deployment roadmaps.
- Champion and enforce exceptional engineering standards for code quality, system efficiency, and security in a prototyping environment.
Requirements
- BS in Software Engineering, Computer Science, or equivalent field of study
- 5+ years of postgraduate experience in software development
- Experience developing highly-available, performant, scalable ML systems, including large-scale data processing pipelines.
- Strong expertise in Python (including the ML stack: PyTorch, TensorFlow, JAX, NumPy, Pandas)
- Long, successful history of driving the full ML lifecycle: from initial data exploration and hypothesis testing to architecture, model training, evaluation, and production deployment.
- Deep proficiency in MLOps and software best practices, including CI/CD for ML, experiment tracking (e.g., Weights & Biases, MLflow), automated testing, and version control for both code and datasets.
Benefits
- Competitive salary, equity and annual bonus
- 401k matching at 50% up to IRS maximum contribution
- Unlimited PTO plus a summer and winter break (one week each)
- Twelve weeks of fully paid parental leave in the US, with another 8 weeks for birthing parents
- $750 equipment, software, and office furniture budget
- $100 per month for wellness (physical or mental) and $100 for home office bills
- Top-notch medical, dental and vision insurance for you and your dependents with all premiums covered at 95% for employees
- Family Planning support (fertility, surrogacy, adoption) through Carrot
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