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Machine Learning Engineering Lead
1 week ago
Job Overview:
This role is responsible for establishing, expanding, and maintaining developing and maintaining ML Models and associated data flows, for use cases in PoC, MVP or operationalization state.
Job Scope:
- Ensure the functionality of ML pipelines and associated data pipelines for structured and non-structured data to draw detailed and actionable conclusions
- Conduct regular testing and enhancement of data pipelines to guarantee access for qualified users and data scientists
- Ensure data availability and accessibility in the central repository, and perform end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations
- Work with large, complex data sets and solve difficult, non-routine error reports in a timely manner
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, etc.
- Build the infrastructure for ML experimentation and operationalization using repeatable ML pipelines
- Develop comprehensive understanding of data structures and metrics, advocating for changes where needed for both products' development and sales activity
- Collaborate with cross-functional teams across disciplines such as platform engineering, data engineering
MINIMUM QUALIFICATIONS, EXPERIENCE AND SKILLS REQUIREMENTS:
**QUALIFICATIONS**
Essential:
- Bachelor's degree in Computer Science/Engineering or any relevant field or equivalent work experience accepted
Desirable:
- Master's degree in Computer Science/Engineering or any relevant field would be beneficial
- Certification as a data scientist (Azure Data Scientist or similar)
**YEARS OF EXPERIENCE**
Essential:
- 4+ years of relevant experience within particular area of expertise '“ Data Science field
Desirable:
- 5-6 years of relevant experience within particular area of expertise '“ Data Science field
**SKILLS**
- Working knowledge of Machine Learning / Data Science development tool and capabilities on MS Azure platform (Azure ML, Databricks)
- Working knowledge of containerization using Docker/Kubernetes for creating ML Experimentation environments
- Basic knowledge of data transformation tools (ADF, Databricks)
- Experience in manipulating, processing and extracting value from large disconnected datasets
- Proficiency in at least one of the programming languages such as Python, C/C++, Java, or similar programming language
- Working knowledge of Agile Development setup using Agile & DevOps tools
- Excellent written and verbal communication skills for coordinating across teams
Desirable:
- Working Knowledge of MLOps
- Demonstrated strength in data modeling, ETL development, and data warehousing.
- Proficiency in distributed databases and query languages such as SQL or HQL (Snowflake)
- Experience building and optimizing '˜big data' data pipelines, architectures and data sets
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