Staff Machine Learning Operations Engineer
Top Benefits
About the role
Who you are
- You’ll bring broad experience with infrastructure for automated training, evaluation, and maintenance of trained models; systems for efficient inference on trained models; and practices for versioning dataset and models
- Ideal candidates will bring a blend of experience with highly-automated, stable MLOps pipelines for highly-available systems, and scrappy ad-hoc pipelines for R&D projects
- Most importantly, you’ll bring a track record of working in a fast-moving software development team, exploring new technologies, and solving problems across an entire software stack
- 7+ years of experience with MLOps fundamentals:
- Automated training, evaluation, and retraining loops
- Dataset and model versioning tools, Weights & Biases preferred
- Systems for serving inference
- Build end-to-end ML pipeline using industry-standard tools
- Deep experience with at least one major cloud provider. GCP preferred
- Experience with managing complex data governance requirements
- Familiarity with MLOps architectures and best practices for LLMs and Agentic systems
- 3+ years of experience with infrastructure as code management of public cloud providers. Familiar with terraform. GCP preferred
- Familiarity with building and maintaining CI/CD pipelines for ML systems
- 3+ years of experience with Python, with strong knowledge of software design principles
- Familiarity with building data pipelines or data processing systems at scale, including orchestration tools like Airflow
- Excellent communication and collaboration skills, with the ability to effectively influence a cross-functional team
- Domain experience in advanced materials, drug discovery, cheminformatics, or other areas of chemistry or biology, especially experience with AI systems applied to these domains
- Experience with AI applications in knowledge graphs
- Experience profiling and optimizing GPU usage in MLOps applications
What the job involves
- SandboxAQ is seeking a Staff MLOps engineer to mature our MLOps practices by building out infrastructure and application code, as well as embedding with R&D teams to champion adoption of your tools and gather feedback to improve them
- In this role, you’ll be working closely with data engineers, software developers, research scientists, and ML scientists to deliver solutions at the frontier of AI in chemistry and the life sciences
- This is a hands-on-keyboard role, however it includes the opportunity to build and lead a team of MLOps engineers for interested candidates
- Mature our MLOps practice by defining processes and building fundamental tooling
- Embed closely with R&D teams to assist in delivering project goals and drive adoption of practices and tooling
- Drive the design and implementation of complex, security-sensitive data processing and storage systems with complex tenancy and data isolation requirements
- Collaborate closely with the product team and internal stakeholders in all phases of software development to validate the solutions you propose and implement
- In collaboration with the rest of the engineering team, build and manage infrastructure for SandboxAQ’s simulation and data platform
- Review code and participate in design and architectural discussions
Benefits
- Stock options
- Unlimated vacation (PTO) and flexible work culture
- Company-wide winter and summer breaks to unwind
- Best-in-class health plans: Medical, dental and orthodontics, and vision
- Family planning and fertility benefits
- Military leave
- 100% paid parental leave
- 401k with company matching
- Education stipends
- Financial wellness resources
About SandboxAQ
In the tech and data intelligence worlds, a sandbox is where innovation is born. It’s a place where the brightest free-thinking minds from across disciplines come together to reimagine what’s possible. A collaborative environment where the whole is infinitely greater than the sum of the parts.
At SandboxAQ, this forward-looking vision is core to everything we do. It’s how we became who we are and it’s how we know our solutions can shift the way your business competes in tomorrow’s marketplace. As the world enters the third quantum revolution, AI + Quantum software will address significant business and scientific challenges. SandboxAQ is a B2B company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) deliver critical advances in life sciences, financial services, navigation, cyber and other sectors. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors including T. Rowe Price, Eric Schmidt, Breyer Capital, Guggenheim Partners, Marc Benioff, Thomas Tull, Paladin Capital Group, and others.
Staff Machine Learning Operations Engineer
Top Benefits
About the role
Who you are
- You’ll bring broad experience with infrastructure for automated training, evaluation, and maintenance of trained models; systems for efficient inference on trained models; and practices for versioning dataset and models
- Ideal candidates will bring a blend of experience with highly-automated, stable MLOps pipelines for highly-available systems, and scrappy ad-hoc pipelines for R&D projects
- Most importantly, you’ll bring a track record of working in a fast-moving software development team, exploring new technologies, and solving problems across an entire software stack
- 7+ years of experience with MLOps fundamentals:
- Automated training, evaluation, and retraining loops
- Dataset and model versioning tools, Weights & Biases preferred
- Systems for serving inference
- Build end-to-end ML pipeline using industry-standard tools
- Deep experience with at least one major cloud provider. GCP preferred
- Experience with managing complex data governance requirements
- Familiarity with MLOps architectures and best practices for LLMs and Agentic systems
- 3+ years of experience with infrastructure as code management of public cloud providers. Familiar with terraform. GCP preferred
- Familiarity with building and maintaining CI/CD pipelines for ML systems
- 3+ years of experience with Python, with strong knowledge of software design principles
- Familiarity with building data pipelines or data processing systems at scale, including orchestration tools like Airflow
- Excellent communication and collaboration skills, with the ability to effectively influence a cross-functional team
- Domain experience in advanced materials, drug discovery, cheminformatics, or other areas of chemistry or biology, especially experience with AI systems applied to these domains
- Experience with AI applications in knowledge graphs
- Experience profiling and optimizing GPU usage in MLOps applications
What the job involves
- SandboxAQ is seeking a Staff MLOps engineer to mature our MLOps practices by building out infrastructure and application code, as well as embedding with R&D teams to champion adoption of your tools and gather feedback to improve them
- In this role, you’ll be working closely with data engineers, software developers, research scientists, and ML scientists to deliver solutions at the frontier of AI in chemistry and the life sciences
- This is a hands-on-keyboard role, however it includes the opportunity to build and lead a team of MLOps engineers for interested candidates
- Mature our MLOps practice by defining processes and building fundamental tooling
- Embed closely with R&D teams to assist in delivering project goals and drive adoption of practices and tooling
- Drive the design and implementation of complex, security-sensitive data processing and storage systems with complex tenancy and data isolation requirements
- Collaborate closely with the product team and internal stakeholders in all phases of software development to validate the solutions you propose and implement
- In collaboration with the rest of the engineering team, build and manage infrastructure for SandboxAQ’s simulation and data platform
- Review code and participate in design and architectural discussions
Benefits
- Stock options
- Unlimated vacation (PTO) and flexible work culture
- Company-wide winter and summer breaks to unwind
- Best-in-class health plans: Medical, dental and orthodontics, and vision
- Family planning and fertility benefits
- Military leave
- 100% paid parental leave
- 401k with company matching
- Education stipends
- Financial wellness resources
About SandboxAQ
In the tech and data intelligence worlds, a sandbox is where innovation is born. It’s a place where the brightest free-thinking minds from across disciplines come together to reimagine what’s possible. A collaborative environment where the whole is infinitely greater than the sum of the parts.
At SandboxAQ, this forward-looking vision is core to everything we do. It’s how we became who we are and it’s how we know our solutions can shift the way your business competes in tomorrow’s marketplace. As the world enters the third quantum revolution, AI + Quantum software will address significant business and scientific challenges. SandboxAQ is a B2B company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) deliver critical advances in life sciences, financial services, navigation, cyber and other sectors. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors including T. Rowe Price, Eric Schmidt, Breyer Capital, Guggenheim Partners, Marc Benioff, Thomas Tull, Paladin Capital Group, and others.