- Company Name
- Ctrl
- Job Title
- Senior Software Engineer
- Job Description
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Job title: Senior Software Engineer (AI/ML & Platform Engineering)
Role Summary: Lead architect and engineer overseeing the design, deployment, and scaling of AI/ML models for aerial and geospatial data, while building secure, cloud-native backend services that power integrated energy, defense, and infrastructure platforms. Combine hands‑on coding with strategic mentorship, driving innovation toward director/CTO readiness.
Expactations:
- Deliver production‑grade multimodal AI models using PyTorch, CV, and GIS data sources.
- Build scalable, event‑driven backend services on AWS, Kubernetes, and microservices.
- Mentor a cross‑functional team of engineers and data scientists.
- Align technical roadmaps with product strategy and executive priorities.
- Represent the organization at conferences and contribute to the broader AI/ML community.
Key Responsibilities:
- Design and implement computer vision and multimodal AI models for RGB, thermal, LiDAR, SAR, and hyperspectral imagery.
- Build standardized data pipelines for drones, satellites, and IoT devices, enabling high‑throughput inspection and mapping workflows.
- Architect and scale backend APIs, microservices, and cloud workflows (EC2, Lambda, S3, RDS, API Gateway, Terraform).
- Optimize geospatial data infrastructure (PostgreSQL/PostGIS, Elasticsearch) and develop streaming/event‑driven architectures (Apache ActiveMQ, Kafka).
- Establish CI/CD pipelines, containerization, and observability (Docker, Kubernetes, Sentry, Kibana).
- Lead R&D initiatives, evaluate emerging technologies, and publish findings or patents.
- Mentor engineers, foster a culture of inclusion, and prepare for senior leadership advancement.
Required Skills:
- Deep learning expertise (PyTorch, CV, multimodal, generative models).
- Backend development in Java, Spring, and cloud‑native architectures.
- Data engineering with PG/PostGIS, Elasticsearch, GIS APIs, GDAL.
- Event‑driven and distributed systems (ActiveMQ, Kafka, microservices).
- Cloud proficiency: AWS services (EC2, Lambda, S3, RDS, API GW, Terraform).
- DevOps: CI/CD, Docker, Kubernetes, monitoring (Sentry, Kibana).
- Strong communication, mentorship, and strategic thinking.
- Publications, patents, or open‑source contributions in AI/geospatial a plus.
Required Education & Certifications:
- Master’s or PhD in Computer Science, Engineering, AI/ML, or a related field.
- 10+ years of professional experience, including 5+ in team leadership and 8+ in deep learning for CV/geospatial.
- Optional: AWS Certified Solutions Architect / Developer, TensorFlow Developer, or equivalent credentials.