Remote (EST hours)
We currently have an opening for an ML engineer/data scientist with experience in building and deploying production predictive systems. The ideal candidate will have strong experience with ML models created using Python, have working knowledge of data pipelines and experience building production-ready ML models in Microsoft Azure. Previous experience with the Agile SDLC methodology is preferred.
As an ML Engineer you bring:
- Strong problem-solving skills
- Commitment to delivery
- Excellent communication skills and a desire to collaborate openly within a fast-moving team
- A deep desire to learn and apply technology in a pragmatic way to create client value
- Experience designing and building systems that are maintainable, evolvable and highly tested.
As an ML Engineer you will be responsible for:
- Explore and develop use cases for development based on business needs identified by the product owner
- Develop and productionize Azure ML models by identifying opportunities to increase efficiencies and create new value
- Devise performance improvement and maturation strategies for models based on feature performance, in-situ model performance and stakeholder feedback
- Support development and improvement of shared libraries for data scientists
- Optimize ML models for deployment, improving sustainability and performance
- Contribute to improvement of the metadata catalog, A/B testing frameworks, and other associated toolkits
- Work cross-functionally in AI/ML team to drive continued improvement of processes and deliver the next set of improvements
- Partner with other functions to drive long-term roadmap, improved capabilities, and share results/processes with the organization more broadly.
- 3-5 years of hands-on experience in an enterprise environment.
- Experience working with deep learning and NLP toolsets, including new generative AI technologies such as Azure OpenAI and ChatGPT
- Knowledge of common MLOps pipeline patterns and associated technologies
- Experience with deep learning using PyTorch, Tensorflow, Keras
- Knowledge of production systems, experience designing sustainable ML model deployments and driving those requirements to reality
- Experience with scaling production models using containerization
- Fluency in Python; some experience with production pipeline coding (Java/Go/Scala)
- Master’s degree in Computer Science, Computational Science, or related field is preferred.
Additional Preferred Skills:
- Generative AI technologies and Azure OpenAI deployment
- Experience working with Agile methodologies and frameworks
- Experience working in Azure cloud and Azure Machine Learning.