Senior Software Engineer developing machine learning geospatial products for Planet. Collaborating with engineers and scientists on innovative remote sensing analytics.
About the role
- Design, build, and maintain infrastructure, pipelines, and tooling to deploy, monitor, and scale ML models in production
- Build and manage CI/CD pipelines for machine learning models
- Automate model training, testing, and deployment workflows
- Design and maintain scalable infrastructure for ML workloads (cloud, on-prem, or hybrid)
- Optimize resource utilization across GPUs/CPUs for inference and training
- Implement monitoring solutions for model performance, data drift, and system health
- Establish alerting and rollback mechanisms for production ML systems
- Work closely with ML engineers to operationalize ML models
- Partner with DevOps and software engineering teams to align ML infrastructure with enterprise standards
- Ensure reproducibility, versioning, and traceability of models and datasets
- Support compliance with data protection and security regulations
Requirements
- Bachelor’s or Master’s in Computer Science, Data Science, AI/ML, or related field (or equivalent experience)
- Strong proficiency in Python
- Experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn
- Experience with containerization and orchestration: Docker, Kubernetes
- Hands-on with cloud platforms: AWS, Azure, GCP and their ML services
- Familiarity with CI/CD tools: GitHub Actions, Jenkins, GitLab CI
- Knowledge of data versioning & workflow orchestration tools: MLflow, DVC, Airflow, Kubeflow
- 2–5 years in MLOps, DevOps, or ML engineering roles
- Experience deploying ML models at scale in production environments
- Candidates with strong DevOps background and mentality who are exploring MLOps will be considered
- Strong problem-solving and debugging skills
- Ability to communicate complex technical concepts to technical and non-technical stakeholders
- Ability to perform market research on MLOps platforms and defend tool selections through presentations
- Collaborative mindset with focus on cross-team alignment
- Continuous learner, staying up to date with ML, DevOps, and cloud technologies
Benefits
- Competitive compensation, ticket restaurant card, and annual bonus programs
- Cutting-edge IT equipment, mobile and data plan
- Modern facilities, free coffee and beverages, indoor parking, and company bus
- Private health insurance, onsite occupational doctor, and workplace counselor
- Flexible working model, hybrid benefits & home equipment benefits
- Onsite gym, wellness facilities, and ping pong room
- Career and talent development tools
- Mentoring, coaching, personalized annual learning and development plan
- Employee referral bonus, regular wellbeing, ESG and volunteering activities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
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PA
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