Engineer: Machine Learning III

Qualifications and experience:

- 4 to 6 years Machine Learning and Software Engineering experience

- Strong analytical and problem-solving skills

- Expert in Python and SQL

- Experience with modern software development best practices, e.g.

- Agile software development

- Code reviews

- Unit testing

- Version control, e.g. git

- CI/CD

- Experience with microservice architectures

- Experience working in an agile team

- Experience with ML frameworks and tools (e.g. pandas, NumPy, scikit-learn, TensorFlow, Pytorch, Spark MLlib)

- Experience with modern ETL, compute and orchestration frameworks, e.g. Apache Spark, Apache Flink, Apache Kafka, etc.

- Development experience in both Windows and Linux

- Experience with container technologies, e.g. Docker, Kubernetes

- Experience in building machine learning or AI systems

- Proficiency in R language

- Experience deploying models to production

- Experience building distributed systems

- Experience with NoSQL databases

- Experience working with ML platforms, e.g. MLflow, Kubeflow, etc.

- Experience working with Data Science platforms, e.g. Dataiku, Domino, etc.

- Experience with cloud-based infrastructure, e.g. Azure, AWS, GCP; (AWS preferred)

- A relevant degree in Information Technology - Computer Science or Engineering Other

- A relevant degree in Information Technology - Computer Science or Engineering - Other

Knowledge of:

- Object oriented and functional programming in Python

- Modern software development practices

- Database querying using SQL

- Data science life cycle

- Machine learning concepts

- Machine learning model life cycle

- Microservice architectures

Ideal:

- Data Science lifecycle

- Distributed system design

- Big data storage and processing solutions

- Machine learning model architectures

Skills:

- Analytical Skills

- Decision making skills

- Planning, organising and coordination skills

- Problem solving skills

- Researching skills

Originally posted on Himalayas