Machine Learning Engineer 3

A senior-level data science role responsible for designing, developing, and implementing advanced time series forecasting models to predict future trends based on historical data.

Role & responsibilities

• Lead the design and development of complex time series forecasting models using various techniques like ARIMA, Exponential Smoothing, Seasonal Decomposition, Prophet, LSTM networks, and other cutting-edge algorithms based on business needs.
• Thoroughly analyze large volumes of time series data to understand patterns, trends, seasonality, and potential anomalies.
• Fine-tune LLM models and work on time series models.
• Prototype and develop solutions for ML/LLM operations and Applied AI.
• Lead a team of data scientists and engineers focused on time series forecasting projects.
• Provide technical guidance, mentorship, and knowledge transfer to team members on time series analysis techniques and best practices.

Qualifications:

• Minimum of 5 years of experience in the AI/ML space.
• Proficiency in Deep Learning and AI frameworks.
• Strong foundation in data structures and statistics.
• Familiarity with SQL and databases.
• Excellent coding skills in Python and machine learning libraries (Scikit-learn, TensorFlow, PyTorch).
• Hands on Experience with Generative AI, LLMs, and time series models.
• Strong proficiency in statistical analysis and time series forecasting techniques (ARIMA, Exponential Smoothing, Prophet, etc.)
• Familiarity with cloud computing platforms (AWS, Azure, GCP) for data storage and model deployment.
• Hands-on experience building and deploying APIs or large-scale systems.

Disclaimer:

The above information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications. Comcast is an EEO/AA/Drug Free Workplace. Comcast is an equal opportunity employer.