Staff Data Engineer

Who We Are  

Bold. Unapologetic. Hardworking. We are building something special.  We transform energy into high-value compute with superior efficiency at scale.  Today, that means powering and securing the Bitcoin Network.  Tomorrow, that could also include powering workloads in AI, HPC and other forms of high-value compute.

Core Scientific is one of the largest bitcoin miners and bitcoin mining hosts in North America.  Our mission is to accelerate digital innovation by scaling high-value compute rapidly, efficiently and responsibly.  Our proprietary software stack optimizes bitcoin mining, pushes firmware, and monitors all aspects of our operations, ensuring we and our customers generate the highest possible ROI on our hardware investment.

But what makes us different from others in our industry?  We own and manage our own infrastructure.  That puts us in control of our operations and gives us an advantage that translates into higher productivity and efficiency.  It also gives us the ability to deploy rapidly the innovations developed by our deep tech team.

Come join us as we continue our journey and accelerate yours.  We seek smart, creative, collaborative minds, who work hard and fast.

Intrigued? Then apply and be a part of something truly special at Core Scientific.

Title  
Staff Data Engineer

Reports To  
Sr. Manager, Data Engineering 

The Job   

Engineer responsible for designing and building end-to-end large-scale ML systems for forecasting, classification, regression, and predictive modeling. Ideal candidate will have deep expertise in building scalable solutions with proficiency in AI/ML frameworks, Python, SQL, big data processing, distributed computing, and MLOps.
Responsible for the full machine learning lifecycle, from data ingestion and feature engineering to model development, deployment, and monitoring. Applying cutting-edge machine learning techniques and collaborating with cross-functional teams to develop impactful ML solutions.

Responsibilities:    

• Develop and deploy scalable ML pipelines for feature engineering, training, tuning, evaluation, and inference.
• Leverage advanced time series analysis and classification techniques to enhance model precision and boost predictive performance.
• Build efficient and scalable ML models for real-time inference and batch processing in distributed computing environments.
• Collaborate with cross-functional teams (data engineers and product teams) to define ML system requirements and integrate ML models into business workflows.
• Drive research and innovation by exploring new ML techniques and incorporating the latest advancements in deep learning, transformers, LLMs, statistical modeling, and ML algorithms.
• Design and implement agent-based systems that combine machine learning, generative AI for autonomous decision-making and workflow automation.
• Develop intelligent agents capable of interacting with users and other systems to streamline operations, support dynamic content creation, and facilitate real-time problem solving.
• Establish evaluation protocols for agent behaviors to ensure alignment with business objectives.
• Foster open, respectful, and professional communication directly within the team, with co-workers/ teammates, and leaders across the organization. 
• Performs other duties as assigned. 

Qualifications:  

• MS/PhD in Computer Science, Data Science, Information Sciences, or related field.
• 5+ years of hands-on experience in machine learning, with a proven track record of designing, building, and maintaining end-to-end ML systems in production environments.
• Experience with implementing LLM-based solutions including LLM fine-tuning and LLM Evaluation.
• Demonstrated experience in generative AI technologies such as LangChain and LangGraph to architect, develop and deploy agent systems including Retrieval Augmented Generation (RAG) frameworks.
• Proficiency with ML frameworks like TensorFlow, PyTorch, Scikit-learn, or similar.
• Proficiency in Python (PySpark, NumPy, Pandas, Scikit-Learn) and SQL for data manipulation and model development.
• Deep understanding of forecasting techniques, including ARIMA, Prophet, LSTMs, Transformers, and advanced statistical models.
• Strong experience in classification models, supervised learning, feature engineering, and hyperparameter tuning.
• Strong experience in Databricks, Apache Spark, MLflow, and distributed computing environments.
• Experience with MLOps best practices, including versioning, monitoring, and CI/CD for ML models.

Location 

To be considered for this role, you must reside near the following locations: Miami, FL or Austin, TX

Travel  

Frequent travel is required as needed. 

Work Environment 

This job operates in a professional office environment and routinely uses standard equipment such as laptop computers and smartphones.

Physical Demands

While performing the duties of this job, the employee is frequently required to sit, stand, walk, use hands, and lift up to 20 pounds.

Position Type/ Expected Hours of Work

This is a full-time, onsite position. General hours and days of work are Monday through Friday, 8:00 a.m. to 5:00 p.m. some nights and weekends may be required.

Supervisory Experience (Yes or No) 

No