Leveraging AQ - the powerful compound effects of AI + Quantum technology
Senior Machine Learning Engineer, AI Generation Engine
Location
United States
Posted
5 days ago
Salary
$131.2K - $246K / year
Seniority
Senior
Job Description
Senior Machine Learning Engineer, AI Generation Engine
SandboxAQ
• 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.
Job 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
Related Guides
Related Job Pages
More Machine Learning Engineer Jobs
• End-to-End Product Engineering: Rapidly prototype and scale full-stack applications, ensuring seamless integration between UI, business logic, and ML inference. • Architectural Leadership: Design modular, extensible system architectures that support rapid iteration without accruing technical debt. • Technical Governance: Lead code reviews across the stack and serve as escalation point for engineering, infrastructure, and security decisions. • Risk & Remediation: Identify scalability bottlenecks and security vulnerabilities and present remediation strategies. • Bridge Research & Product: Translate experimental ML techniques into production-ready features. • Infrastructure & Compliance: Design infrastructure aligned with government audit requirements (e.g., HIPAA, FedRAMP). • Security-First Development: Implement IAM and secure data practices across the lifecycle. • AI-First Product Ownership: Drive conception and execution of AI-first products, maintaining a strong bias toward applying state-of-the-art capabilities in production environments.
Pessoa Engenheira de Machine Learning – Especialista II
Grupo BoticárioCriamos oportunidades para a beleza transformar a vida das pessoas, e assim transformar o mundo ao nosso redor.
• Construção de pipelines de Machine Learning de ponta a ponta: incluindo preparação de dados, otimização de código, automatização de rotinas de treino e predição de modelos; • Monitoramento de métricas de qualidade, eficiência, custo e uso de produtos de dados; • Liderança técnica no processo de MLOps do time, definindo boas práticas de desenvolvimento e sustentação de soluções; • Desenvolvimento de arquiteturas em nuvem para soluções de dados e IA (GCP, AWS, Azure); • Construção de pipelines de dados com modelos de Gen AI embarcados (ex: preparação de dados não estruturados para estruturados); • Desenvolvimento de pilotos junto à área para prototipação de conceitos e prova de valor.
AI/ML Engineer – SC Cleared
Cloud BridgeHarness the full potential of AWS with award-winning Premier Partner, Cloud Bridge
• Attend technical and IT meetings to identify inefficiencies and automation opportunities • Translate business pain points into clear AI/ML use cases and delivery plans • Design and build LLM- and ML-based solutions to improve internal processes • Deploy automation tools and AI agents that enhance quality, speed, and consistency • Collaborate with architects and stakeholders, owning delivery of well-scoped initiatives
• Rapidly prototype and build full-stack tools and visualizations to support researchers and entrepreneurs. • Design, implement, test, and debug code across front-end, back-end, and data pipelines. • Collaborate with research teams to translate cutting-edge ML techniques into production-ready solutions. • Work with entrepreneurs and users to gather requirements, incorporate feedback, and iterate on product development. • Develop and optimize robust pipelines for model fine-tuning, evaluation, and deployment. • Establish best practices for reliable and reproducible ML model development. • Contribute to the creation of scalable, high-performance infrastructure for AI-driven products.



