Here at StratumAI, we work towards improving the mining industry using ML to make better resource models, reduce waste, and improve efficiency. We are looking for an adaptable and capable ML Ops Engineer to join our startup’s technical team and help us move towards changing the global mining industry.
You’ll be joining a diverse team of engineers and data scientists to work on building, improving, and maintaining end-to-end machine learning systems. If you are interested in working on ML problems in industry and want to explore novel tools and systems to accurately diagnose and maintain ML systems, then this is the position for you. To be successful, you need exceptional skills in machine learning and software engineering with a healthy dose of curiosity to learn new things on the fly. Interest in working at a growing startup is a must!
- Introducing features and testing frameworks to evaluate models on multiple metrics
- Applying existing ML libraries and frameworks for tasks such as model uncertainty, data uncertainty, and data analysis
- Examining sections of ML workflow for inefficiencies and improving said bottlenecks
- Working on tools to simplify and automate data cleaning, processing, and analysis
- Automating workflows for training, evaluating, and updating models in deployment
- Keeping abreast of developments and best practices
- Understanding of data structures, data modeling and software architecture
- Ability to write robust code in Python
- Proficiency in using Git, love for best practices, interest in making modular and extensible software
- Experience with ML frameworks/libraries (Tensorflow, PyTorch, Jax, sk-learn)
- Strong experience with data analysis/processing libraries such as pandas and numpy
- Self-learner and motivated to pick up new skills
- Outstanding analytical and problem-solving skills
Nice to Have
- Experience working on production machine learning using tools such as KubeFlow, MLFlow, AirFlow, Seldon Core, DVC, Spark, etc.
- Experience in distributed training and performance optimization on GPU’s
- Strong background in probability, machine learning, and data science
- Previous experience working at startups
- Experience working with machine learning in computer vision, NLP, recommender
systems, and scientific applications