"Machine Learning Engineering"

Qualifications

• Description: The candidate should have experience with cloud platforms, particularly Azure, as the company is transitioning towards this platform (Currently a Databricks shop)
• Knowledge of Azure services, including data storage, processing, and machine learning tools, is essential
• Why It's Important: Proficiency in Azure will enable the candidate to effectively manage and deploy machine learning models in the cloud, ensuring scalability and integration with existing infrastructure
• Data Engineering and ETL Skills:
• Description: The candidate must have strong data engineering skills, including experience with SQL Server, ETL processes, and big data technologies
• They should be capable of handling large datasets, ensuring data quality, and preparing data for analysis
• Looking for someone confident in the space to prove to the business that this is a critical role
• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field
• Proven experience in machine learning, data analysis, and statistical modeling
• Proficiency in programming languages such as Python, R, or Java
• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn)
• Strong analytical and problem-solving skills
• Excellent communication and teamwork abilities
• Experience with big data technologies
• Knowledge of cloud platforms (e.g., Azure, Fabric)
• Familiarity with data visualization tools (e.g., Power BI)

Responsibilities

• Why It's Important: Effective data engineering is critical for building robust machine learning models
• The candidate needs to ensure that data is accurately collected, processed, and made available for analysis and model training
• Moving away from relying on external vendors and wants to bring expertise in-house
• The ideal candidate will be responsible for analyzing complex datasets, developing machine learning models, and providing actionable insights to drive business decisions
• This role requires a strong foundation in data science, programming, and statistical analysis
• Analyze large datasets to identify patterns, trends, and insights
• Develop, test, and deploy machine learning models to solve business problems
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions
• Monitor and evaluate the performance of deployed models, making improvements as necessary
• Communicate findings and recommendations to stakeholders through reports and presentations
• Stay updated with the latest advancements in machine learning and AI technologies

Full Description

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Sriven Systems Inc., is seeking the following. Apply via Dice today!

Cloud Platform Proficiency (Azure):

Description: The candidate should have experience with cloud platforms, particularly Azure, as the company is transitioning towards this platform (Currently a Databricks shop). Knowledge of Azure services, including data storage, processing, and machine learning tools, is essential.

Why It's Important: Proficiency in Azure will enable the candidate to effectively manage and deploy machine learning models in the cloud, ensuring scalability and integration with existing infrastructure.

3. Data Engineering and ETL Skills:

Description: The candidate must have strong data engineering skills, including experience with SQL Server, ETL processes, and big data technologies. They should be capable of handling large datasets, ensuring data quality, and preparing data for analysis.

Why It's Important: Effective data engineering is critical for building robust machine learning models. The candidate needs to ensure that data is accurately collected, processed, and made available for analysis and model training.

Long story short: They're trying to build capabilities in-house. Moving away from relying on external vendors and wants to bring expertise in-house. Looking for someone confident in the space to prove to the business that this is a critical role. Look at it as a "prove yourself" role.

Job Description

We are seeking a skilled and innovative Machine Learning (ML) AI Analyst to join our dynamic team. The ideal candidate will be responsible for analyzing complex datasets, developing machine learning models, and providing actionable insights to drive business decisions. This role requires a strong foundation in data science, programming, and statistical analysis.

Key Responsibilities:

Analyze large datasets to identify patterns, trends, and insights.

Develop, test, and deploy machine learning models to solve business problems.

Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.

Monitor and evaluate the performance of deployed models, making improvements as necessary.

Communicate findings and recommendations to stakeholders through reports and presentations.

Stay updated with the latest advancements in machine learning and AI technologies.

Qualifications:

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.

Proven experience in machine learning, data analysis, and statistical modeling.

Proficiency in programming languages such as Python, R, or Java.

Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).

Strong analytical and problem-solving skills.

Excellent communication and teamwork abilities.

Preferred Skills:

Experience with big data technologies.

Knowledge of cloud platforms (e.g., Azure, Fabric).

Familiarity with data visualization tools (e.g., Power BI).