Senior Manager: Ml Engineering
Posted on 2025-03-17
Employer | Recruit-It |
---|---|
Salary | 1 |
Category | Automotive |
Location | Gauteng / Gauteng |
Job Summary
Lead the design, development, and implementation of cutting-edge analytic engines and services, leveraging extensive experience and expertise in machine learning to develop and deploy scalable models, optimize algorithms, and drive data-driven decision-making.
Job Responsibilities
- Develop and maintain a machine learning platform, ensuring it meets the needs of the community and stakeholders.
- Design and build robust inference systems, such as APIs, batch processing, and real-time streaming, to facilitate the deployment and utilization of machine learning models.
- Implement MLOps practices to streamline the deployment, monitoring, and management of machine learning models in production.
- Automate the end-to-end machine learning pipeline, from data ingestion to model deployment and monitoring.
- Ensure the scalability and reliability of the machine learning platform, addressing performance bottlenecks and optimizing resource usage.
- Utilize big data technologies such as Spark, Ray, and Dask to handle large-scale data processing and distributed computing.
- Leverage GPU acceleration to enhance the performance and efficiency of machine learning models, particularly for deep learning tasks.
- Collaborate with cross-functional teams to integrate machine learning solutions into existing systems and workflows.
- Contribute to the development and maintenance of documentation, tutorials, and guides for the machine learning platform.
- Engage with the data science community, participating in discussions, code reviews, and contributions to foster collaboration and innovation.
- Spearheaded best-in-class statistical models and algorithms, building upon previous experiences and learnings.
- Conduct in-depth statistical analysis to extract valuable insights and patterns from complex datasets, contributing to data-driven decision-making.
- Offer actionable insights and advice to stakeholders, utilizing a solid foundation in AI/ML and contributing to the team`s expertise.
- Contribute to the creation of value from enterprise-wide data, assisting in the translation of data into meaningful business solutions.
- Experienced in deploying or contributed to deployment of at least one end-to-end data science solution that has yielded significant value in the organization at an enterprise level.
- Contribute to the shaping of the organization`s AI/ML strategy, aligning it with evolving business needs.
- Assist in transforming data science prototypes into scalable machine learning solutions for deployment.
- Collaborate with experienced team members to design dynamic ML models and systems, incorporating the capability for adaptability and retraining.
- Participate in periodic evaluations of ML systems, ensuring they align with corporate and IT strategies.
- Expert proficiency in programming tools (such as Python, R, etc.) for data manipulation, statistical analysis, and machine learning tasks is essential.
- Demonstrate a profound command over computer science fundamentals, encompassing expert-level knowledge of data structures, algorithms, computability and complexity, and computer architecture.
- Utilize machine learning algorithms and libraries effectively, following established best practices and guidelines.
- Communicate technical concepts effectively to diverse audiences, adapting explanations for non-programming experts.
- Stay informed about the latest tools and techniques, engaging in continuous learning to enhance skills and knowledge.
- Proficiency in cloud computing and hands-on experience with deploying complex data science projects on cloud platforms.
- Collaborate with the team, sharing ideas and insights while conducting experiments and researching best practices.
- Seek opportunities for personal growth and development, actively participating in knowledge-sharing and mentorship.
- Contribute to the achievement of the business strategy, objectives, and values, contributing to the organization`s success.
Essential Qualifications – NQF Level
- Advanced Diplomas/National 1st Degrees
- Matric / Grade 12 / National Senior Certificate
Preferred Qualification
- STEM Qualification
- Engineering, Computer Science, Econometrics, Mathematical Statistics, Actuary Science
- Masters or Doctorate will be an added advantage
Preferred Certifications
- Cloud (Azure, AWS), DEVOPS or Data engineering certification.
- Any Data Science certification will be an added advantage, Coursera, Udemy, SAS Data Scientist certification, Microsoft Data Scientist.
Minimum Experience Level
- MS/PhD in STEM or related technical discipline
- 7 years’ plus experience in a data science or software engineering role.
- Deep knowledge of machine learning, statistics, optimization or related field.
- Knowledge of Graph Database technology will be a major advantage
- Excellent written and verbal communication skills along with strong desire to work in cross functional teams.
- Attitude to thrive in a fun, fast-paced start-up like environment
Technical / Professional Knowledge
- Data Mining
- Data analysis
- Statistical Analysis
- Supervised Learning
- Big Data Technologies
- Unsupervised Learning
- NLP
- Deep Learning
- Feature Engineering/Selection
- HyperParameter Tuning
- Programming
- Model Deployment/Monitoring
- MLOps
- API Development
- Inference Systems
- GPU Utilization
- Distributed Computing (Spark, Ray, Dask)
- Automation of ML Pipelines
- Scalability and Reliability Engineering
- Cloud Computing
- Documentation and Tutorials Development
- Graph Databases
- PostgreSQL, Redis
Behavioral Competencies
- Decision Making
- Innovation
- Technical/Professional Knowledge and Skills
- Customer Focus
- Applied Learning
- Improvement Continuous Improvement
Senior Manager: Ml Engineering position available in Gauteng, Gauteng. This job position was posted by Recruit-It. The job has been posted as a char8000 ad on 2025-03-17 at 01:04:11 in the Automotive category
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