Performance Assurance Machine Learning Engineer

Intelliswift$156K — $166K *
Plano, TX 75025In-Person
Telecommunications & Hardware
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years of experience in Data Science, Analytics, or Engineering
  • 3-5 years of experience with large scale ML systems
  • Strong programming in Python, R, SQL, and Spark
  • Graduate degree in Computer Science, Data Science, or a related field preferred
  • Experience with cloud development using AWS/Azure/Google
  • Proficient in machine learning techniques including Neural Networks
  • Experience in data visualization and statistical analysis

Responsibilities

  • Analyze deployed network elements under guidance from senior engineers
  • Query databases to extract and analyze data for network performance issues
  • Collaborate across teams to ensure accurate and operationally useful ML outputs
  • Utilize A/B testing and statistical models for performance analysis
  • Communicate key findings using visualizations and reports
  • Define metrics and KPIs for operational insights
  • Prototype use cases and implement automation for efficiency

Benefits

  • Fully onsite work environment
  • Opportunity to work with cutting-edge technologies in AI and ML
  • Involvement in 4G/5G network infrastructure projects
  • Collaboration with diverse, multidisciplinary teams
  • Potential for professional growth in a dynamic industry
Full Job Description
Pay rate range- $75/hr. - $80/hr
Fully Onsite

Job Description:

Top skills:
-Data Modeling
-Machine Learning
-Artificial Intelligence

KEY RESPONSIBILITES/REQUIREMENTS:
As a Performance Assurance Machine Learning Engineer, you will work under the coaching of Senior and Lead engineers of the Data Science & Tools Team to analyze Client's deployed network elements. You will utilize skills to query databases to extract data, use skills in Python or R to analyze data such that you can identify 4G/5G network infrastructure and performance issues and build prediction models, ad-hoc tools, and dashboards to communicate your findings with your team and peers

Specific Responsibilities include:
• 7+ years of professional experience in Data Science, Data Analytics, and/or Data Engineering with abilities to work with large datasets using demonstrated statistical, predictive modeling and machine learning methods.
• 3-5 years demonstrated experience on designing, deploying, and maintaining large scale ML systems in a production environment.
• Work closely with the internal and external stakeholders to explore relationships of 4G/5G KPI measurements and targets (KPI, KQI) for 4G/5G RAN product acceptance and performance monitoring.
• Collaborate with RF engineers, network engineers, data scientists, platform engineers, product teams, and operations stakeholders to ensure ML outputs are technically accurate, interpretable, and operationally useful.
• Utilize A/B testing, statistical, and machine learning models to build robust mechanism for product & feature performance analysis, for evaluation of new product & SW releases and 3rd party product evaluation.
• Aid in product & feature performance analysis, evaluation of new product & SW releases and 3rd party product evaluation using analytics/data science to drive intelligent business decisions.
• Work with the team to proactively define and interpret data/metrics/KPIs, analyze results, and provide insights to determine operational impact, trends and opportunities for all the 4G/5G RAN products.
• Prototyping use cases, implementing automations, and developing tools to support and augment manual or repetitive efforts.
• Communicate key findings to stakeholders using visualizations and/or other suitable methods.
• Excellent verbal and written communication skills to communicate technical and complex concepts in an easy-to-follow progression.
• Able to compile analysis output and findings into a succinct story for technical and non-technical audiences.
• Adapt to changes in a dynamic business environment and, support management initiatives.

Background & Competencies Required:
• Graduate Degree in Computer Science, Statistics, Data Science or a related Data Engineering with 7+ years of professional experience is preferred.
• Programming experience: Python & Spark (preferred) and/or other languages such as R , SQL, Hive, Spark, Javascript, Visual Basic, C++, shell scripting in a linux or IDE environment such as VSCODE, Jupyter, RStudio, etc.
• Cloud Development Experience - AWS/Azure/Google utilizing cloud providers such as Databricks or Snowflake
• Machine learning expertise: GLM Regression (Linear, Logistic, Multinomial), Decision Tree (including Boosted Trees, Random Forest), kMeans/Hierarchical Clustering, Principle Component Analysis, t-SNE, Neural Networks such as transformers and auto-encoders, Bayesian Regression, and Times Series Modeling.
• Experience using data with high-volume (1TB+) & high-dimensionality (500+ variables per schema), especially within a big data framework (HaDoop, Citus, MongoDB, etc).
• Experience performing Data Wrangling, Exploratory Data Analysis (EDA), Correlation Analysis, Statistical Methodologies (distributions, hypothesis testing, confidence intervals) & Significance Testing, A/B Testing.
• Experience with MLOPS concepts and environments such as MLFLOW a plus.
• Experience with basic linux administration and software development in a linux environment.
• Experience in hardware resource management and configuration - CUDA, Docker, KubeFlow, Kubernetes, etc a plus
• Must possess qualities of being curious and eagerness to learn .
• Experience with data visualization and ability to quickly grasp statistical methods, and methodologies. Maintain a strong command of current data analytics technology trends, including emerging paradigms and practices.
• Demonstrated research and problem solving skills via prior work experience. Experience with wireless infrastructure provider and/or operator is desired.
• Technical knowledge of any wireless technology & procedures including CDMA/EVDO/LTE/Volte and/or 5G a plus.
• Experience with evaluating service performance trends and proactively defining RAN system performance related issues a plus.
• Experience of software version control, coding best practices, and use of development management software such as github, bitbucket, etc is desired.
• Must have a strong work ethic, integrity and work extremely well independently or in a team environment.

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