Machine Learning Engineer

Experience

Minimum:

Proven experience in:

2+ yrs software development experience

Strong analytical and problem-solving skills

Expert in Python and SQL

Experience with the 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

Ideal:

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; ideally AWS

Qualifications (Minimum)

A relevant qualification in Information Technology - Computer Science or Engineering

Qualifications (Ideal or Preferred)

Masters Degree in Information Technology - Computer Science or Engineering - Other

Knowledge

Min:

Must have knowledge of:

Object oriented and functional programming in Python

Modern software development practices

Database querying using SQL

Data life cycle

Machine learning concepts

Machine learning model life cycle

Microservice architectures

Ideal:

Knowledge of:

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