Responsibilities
- Deploy and maintain ML models from the data science team
- Design and implement APIs and real-time inference services
- Work with large-scale time-series datasets from vibration and sensor systems
- Improve the performance and reliability of model serving pipelines
- Monitor system health and implement logging, alerting, and fallback mechanisms
- Contribute to architectural decisions and collaborate across teams
Requirements
- 2–4 years of experience in software or machine learning engineering
- Bachelor’s degree in Computer Science, Engineering, or related technical field
- Solid background in math, statistics, and machine learning concepts
- Strong Python skills and experience with ML libraries like scikit-learn or PyTorch
- Experience deploying models in production environments
- Familiarity with event-driven platforms and message queues (e.g., Kafka, Redis Streams)
- Comfort working with streaming or time-series data
Preferred Qualifications
- Experience with containerization (Docker) and cloud deployment
- Exposure to real-time or low-latency systems
- Interest in optimization of inference latency and resource usage
Technical Skills
- Programming: Python, Golang
- ML Libraries: scikit-learn, PyTorch, TensorFlow
- Backend: FastAPI, Flask
- Infrastructure: Kafka, Redis, PostgreSQL, Docker
- ML Ops: Model serving, monitoring, CI/CD pipelines
Top Skills
What We Do
Tractian is a machine intelligence company that offers industrial monitoring systems. Tractian builds streamlined hardware-software solutions to give maintenance technicians and industrial decision-makers comprehensive oversight of their operations. It is democratizing access to sophisticated real-time monitoring and asset operations tools.
Tractian's solutions are used in environments that address a combined total of 5% of global industrial output. The company’s broad market reach is evidenced in its customer base from various industries, such as John Deere, Procter & Gamble, Caterpillar, Goodyear, Carrier, Johnson Controls, and Bimbo, the owner of the brands Little Bites and Thomas Bagels. Tractian's customers see a 6-12x ROI with savings of $6,000 per monitored machine annually on average.
In a major milestone and a first for the industry, Tractian launched the AI-Assisted Maintenance category in the industrial sector. In this new paradigm, artificial intelligence identifies machine problems and suggests preventive actions to be taken, giving invaluable insight and support to maintenance professionals. It is important to highlight that the intent of Assisted Maintenance is firmly rooted in augmenting maintenance professionals to provide more assertive diagnosis with human-in-the-loop feedback.
Tractian's mission is to elevate this category of workers in a highly impactful way. The Assisted Maintenance category will provide unimaginable support for maintenance professionals. By combining shop floor expertise with our technology, maintainers will be able to anticipate and address issues with unprecedented accuracy and speed
