Note: The job is a remote job and is open to candidates in USA. Theoris Services is assisting a client in their search for a Machine Learning Software Engineer to enhance their team. This role focuses on productionizing machine learning models and integrating them into a proprietary application, requiring expertise in Python and ML infrastructure.
Responsibilities
- Transform prototype ML code and experimental scripts into modular, maintainable, and production-grade Python code
- Lead end-to-end onboarding and integration of new machine learning models into the BioNova application
- Configure and manage execution of ML jobs on HPC (High-Performance Computing) clusters and Kubernetes (K8s) environments
- Build and maintain containerized environments and automation scripts to streamline model updates and deployments
- Collaborate with data scientists, ML researchers, and platform engineers to ensure smooth transition from experimentation to production
- Develop and maintain shell scripts for job scheduling, automation, and system management
Skills
- Expert-level Python programming with a focus on writing clean, testable, modular, and scalable code
- Strong hands-on experience with PyTorch
- Proven ability to write Bash/Shell scripts for automation and job orchestration
- Hands-on experience with Docker containerization
- Solid experience running and monitoring jobs on HPC environments (e.g., Slurm) or Kubernetes clusters
- Strong problem-solving skills and attention to detail
- Ability to work independently in a fast-paced, agile environment
- Previous experience in biotechnology, life sciences, or scientific computing environments
- Familiarity with MLOps practices and tools
- Experience with workflow orchestration tools (e.g., Airflow, Kubeflow)
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
Benefits
- Robust Health Insurance
- 401(k) plan
- PTO
- Paid holidays
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