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Senior / Staff Software Engineer

Psivant

Boston (MA)

On-site

USD 90,000 - 150,000

Full time

30+ days ago

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Job summary

An established industry player is seeking a Senior/Staff Software Engineer to lead efforts in computational drug discovery. This role involves designing and optimizing scalable pipelines for molecular simulations using GCP, while fostering a culture of innovation and high-quality code. You will collaborate with scientists and engineers, implement best practices, and mentor junior staff. Join a dynamic team dedicated to pushing the boundaries of drug discovery through cutting-edge technology and cloud computing. If you are passionate about making a difference in healthcare, this opportunity is for you.

Qualifications

  • 5+ years of software engineering experience, especially in cloud computing.
  • Strong proficiency in Python and experience with GCP services.

Responsibilities

  • Design and optimize scalable pipelines for molecular simulations in GCP.
  • Mentor junior engineers and promote software engineering best practices.

Skills

Software Engineering
Cloud Computing
Python
Collaboration
Linux System Administration
Communication Skills
Scientific Applications
Innovation

Education

Bachelor's Degree in Computer Science
Master's Degree in Engineering

Tools

GCP
Git
Docker
Slurm
Kubernetes

Job description

The Senior/Staff Software Engineer at Psivant will be a key contributor to our computational drug discovery efforts. You will be responsible for designing, developing, and optimizing scalable pipelines for molecular simulations within GCP. You will also play a vital role in establishing and promoting software engineering best practices within the team, fostering a culture of innovation and high-quality code.

Responsibilities
  1. Design, develop, and maintain robust and scalable pipelines for molecular simulations in GCP, leveraging services like Compute Engine, Cloud Storage, Dataflow, BigQuery and Kubernetes Engine.
  2. Optimize existing simulation workflows for performance and cost-effectiveness within the cloud environment.
  3. Collaborate with scientists and other engineers to understand requirements and translate them into efficient software solutions.
  4. Champion and implement software engineering best practices, including code reviews, automated testing, and continuous integration/continuous deployment (CI/CD).
  5. Contribute to the development and maintenance of our software infrastructure and tooling.
  6. Proactively identify and address performance bottlenecks and scalability challenges.
  7. Mentor and guide junior engineers, fostering a collaborative and supportive team environment.
  8. Stay up-to-date with the latest advancements in cloud computing, molecular simulation, and software engineering.
Requirements
  1. Bachelors or Masters degree in Computer Science, Engineering, or a related field.
  2. Minimum of 5 years of experience in software engineering, with a focus on cloud computing and scientific applications.
  3. Extensive experience working with GCP, including services like Compute Engine, Cloud Storage, Dataflow, BigQuery, and Kubernetes Engine.
  4. Strong Linux system administration skills, including scripting and troubleshooting.
  5. Proficiency in Python (or an equivalent language) and experience developing complex applications.
  6. Solid understanding of software development lifecycle (SDLC) principles and experience using Git and related tools (e.g., GitHub, GitLab, Bitbucket).
  7. Experience with molecular dynamics simulations or other scientific computing applications is highly desirable.
  8. Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team.
  9. A passion for innovation and a desire to contribute to the advancement of drug discovery.
Additional Qualifications
  1. Experience with job queuing systems such as Slurm.
  2. Familiarity with containerization technologies (e.g., Docker).
  3. Knowledge of high-performance computing (HPC) concepts and techniques.
  4. Experience with machine learning or deep learning applied to drug discovery.
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