Senior Machine Learning Developer

4 days ago

Johannesburg, Gauteng, South Africa SavageOne Pty Full time R1 200 000 - R2 400 000 per year


Position Summary:
The Senior Machine Learning Engineer will play a key role in leading the design, development, and deployment of machine learning solutions. You will collaborate with cross-functional teams to identify business opportunities, develop innovative machine learning models, and implement scalable solutions that drive business value. This role offers a unique opportunity to leverage your expertise in machine learning to tackle challenging problems, mentor junior team members, and contribute to the success of our organization.

Key Responsibilities:

  • Lead the design, development, and deployment of machine learning models and algorithms to solve complex business problems.
  • Collaborate with data scientists, software engineers, and product managers to identify business opportunities and requirements.
  • Conduct exploratory data analysis, feature engineering, and model evaluation to ensure robust and reliable performance.
  • Implement scalable and efficient machine learning pipelines and workflows to process large volumes of data.
  • Stay up-to-date with the latest developments in machine learning research and technologies, and apply them to improve our products and services.
  • Mentor and coach junior machine learning engineers, providing guidance, training, and support to develop their technical skills and knowledge.
  • Collaborate with cross-functional teams to integrate machine learning models into production systems and applications.
  • Document work processes, methodologies, and best practices to facilitate knowledge sharing and collaboration.

Qualifications:

  • Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, or a related field (or equivalent experience).
  • 5+ years of experience in machine learning engineering or related roles, with a proven track record of developing and deploying machine learning solutions in production environments.
  • Strong proficiency in machine learning algorithms, techniques, and frameworks such as TensorFlow, PyTorch, scikit-learn, or Spark MLlib.
  • Experience with big data technologies and platforms such as Hadoop, Spark, or Apache Flink.
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Excellent analytical and problem-solving skills, with a strong attention to detail.
  • Excellent communication and collaboration skills, with the ability to effectively work with cross-functional teams.
  • Demonstrated leadership and mentoring abilities, with a passion for developing and empowering team members.

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