Remote Machine Learning Scientific Software Engineer

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SandboxAQ

💵 $163k-$225k
📍Remote - United States

Job highlights

Summary

Join SandboxAQ's Scientific Software Engineer role to contribute to AI + Quantum solutions and push the envelope on drug development by developing large-scale ML models, writing clean software, and delivering impactful results.

Requirements

  • Required Post-graduate degree in a relevant scientific discipline (for example physics, chemistry, biology, or computer science)
  • At least 5 years professional experience implementing, training, and deploying modern deep learning architectures
  • Experience training on large datasets using distributed compute resources
  • Knowledge of best practices in MLOps and data engineering
  • Professional experience with pytorch-lightning and Weights & Biases (or comparable tools/frameworks)
  • Ability to rapidly write good quality code while not letting the perfect become the enemy of the good

Responsibilities

  • Drive the full lifecycle of new scientific machine learning projects
  • Architecture design, working alongside subject matter experts
  • Model implementation
  • Development of auditable datasets and data-preparation pipelines
  • Training and experimentation
  • Deployment of a productized capability
  • Read and apply current scientific and software-engineering/MLOps best practices literature
  • Maintain and extend existing scientific software packages
  • Work closely with the Engineering Team to build on top of the group’s cloud infrastructure
  • Work closely with the client-facing Drug Discovery Team to run mission-critical computational scientific work
  • Present findings in top-tier scientific and machine-learning venues
  • Foster a work culture of curiosity and kindness

Preferred Qualifications

  • Experience with physical sciences applications of modern machine learning techniques E.g. machine-learned molecular mechanics force fields, protein structure prediction, multi-omics graph inference
  • Experience with the drug discovery and drug development processes
  • Experience writing GPU kernels in CUDA or Triton
  • A professional background that combines time in large enterprises and time in small start-ups

Benefits

  • Competitive salaries
  • Stock options depending on employment type
  • Generous learning opportunities
  • Medical/dental/vision
  • Family planning/fertility
  • PTO (summer and winter breaks)
  • Financial wellness resources
  • 401(k) plans

Job description

Ready to join the AQ era?

SandboxAQ is solving challenging problems with AI + Quantum for positive impact. We partner with global leaders in government, academia, and the private sector to identify applications that would benefit from quantum-based applications to current and future commercial challenges. We engage with customers early and throughout the development process to improve market fit.

Our team’s unique approach enables cross-pollination across a diverse range of fields, from physics, computer science, neuroscience, mathematics, cryptography, natural sciences and more! Our success comes from coalescing diverse talent to create an environment where experimental thinking and collaboration yield breakthrough AI + Quantum solutions. Join a culture where thought leadership, diverse talent, employee engagement, and technological impact will create the next tech uproar.

We are deeply committed to education as a means to advance quantum solutions and computing initiatives. We invest in future talent through internship programs, research papers, developer tools, textbooks, educational talks/events and partnerships with universities/talent hubs to attract multi-disciplinary talent. Our hope is to inspire people from all walks of life to be prepared for the quantum era and encourage a path in STEM.

About the Role

Our team is looking for a Scientific Software Engineer with a specialization in Machine Learning that translates practical science into platform ready tools. This person will help push the envelope on drug development by contributing to projects like multimodal biomolecular structure prediction, accelerated Markov chain Monte Carlo, multi-omics network biology, and machine-learned molecular mechanics force fields. By developing large-scale ML models, writing clean, robust software, and delivering impactful results to client-facing teams, this role is a lynchpin bringing together all the things that make our team successful. What You’ll Do

  • Drive the full lifecycle of new scientific machine learning projects, including:

    • Architecture design, working alongside subject matter experts
    • Model implementation
    • Development of auditable datasets and data-preparation pipelines
    • Training and experimentation
    • Deployment of a productized capability
  • Read and apply current scientific and software-engineering/MLOps best practices literature

  • Maintain and extend existing scientific software packages

  • Work closely with the Engineering Team to build on top of the group’s cloud infrastructure

  • Work closely with the client-facing Drug Discovery Team to run mission-critical computational scientific work

  • Present findings in top-tier scientific and machine-learning venues

  • Foster a work culture of curiosity and kindness

About You

  • Required
    • Post-graduate degree in a relevant scientific discipline (for example physics, chemistry, biology, or computer science)
    • At least 5 years professional experience implementing, training, and deploying modern deep learning architectures (e.g. transformers, diffusion models, graph neural networks)
    • Experience training on large datasets using distributed compute resources
    • Knowledge of best practices in MLOps and data engineering
    • Professional experience with pytorch-lightning and Weights & Biases (or comparable tools/frameworks)
    • Ability to rapidly write good quality code while not letting the perfect become the enemy of the good
    • Desire to work in a fast-paced, sometimes chaotic, team with diverse professional experiences and viewpoints
  • Preferred
    • Experience with physical sciences applications of modern machine learning techniques
      • E.g. machine-learned molecular mechanics force fields, protein structure prediction, multi-omics graph inference
    • Experience with the drug discovery and drug development processes
    • Experience writing GPU kernels in CUDA or Triton
    • A professional background that combines time in large enterprises and time in small start-ups

The US base salary range for this full-time position is expected to be $163k - $225k per year. Our salary ranges are determined by role and level. Within the range, individual pay is determined by factors including job-related skills, experience, and relevant education or training. This role may be eligible for annual discretionary bonuses and equity.

SandboxAQ welcomes all.

We are committed to creating an inclusive culture where we have zero tolerance for discrimination. We invest in our employees’ personal and professional growth. Once you work with us, you can’t go back to normalcy because great breakthroughs come from great teams and we are the best in quantum technology.

We offer competitive salaries, stock options depending on employment type, generous learning opportunities, medical/dental/vision, family planning/fertility, PTO (summer and winter breaks), financial wellness resources, 401(k) plans, and more.

Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Accommodations: we provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know.

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