Staff Data Engineer - AI/ML

Who We Are  

Bold. Unapologetic. Hardworking. Core Scientific transforms energy into high-value compute with unmatched efficiency at scale. The company is publicly owned (NASDAQ: CORZ) and has a market cap of over $7 Billion dollars. 

We power AI, HPC, and other next-generation data center workloads demanding exceptional computing power, in addition to our digital asset mining operations.  We operate nine data centers in seven states housing advanced infrastructure for our customers. 

Core Scientific is a leading provider of infrastructure for high-performance compute in North America. Our mission is to accelerate digital innovation by scaling high-value compute rapidly, efficiently, and responsibly.   

What sets us apart? We have an entrepreneurial culture, a "can-do" and collaborative attitude, and we own and control our infrastructure. These strategic advantages enable us to maintain operational excellence, increase efficiency, and rapidly deploy cutting-edge innovations developed by our team of experts. 

Join us and accelerate your career alongside our groundbreaking journey. We seek smart, creative, and collaborative professionals who thrive in a fast-paced, results-driven environment. 

Ready to be part of something exceptional? Apply today and make an impact at Core Scientific. 

Title 
Staff Data Engineer- AI/ML

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. The 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. 

NOTE: Reasonable accommodation may be made to enable individuals with disabilities to perform the essential responsibilities. 

Qualifications 

• MS/PhD in Computer Science, Data Science, Information Sciences, or related fields is required. 
• 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 required. 
• 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 Miami, FL, or Austin, TX. 

Travel  

Frequent travel may be required as needed. 

Work Environment 

This job is operated in a professional office, warehouse, and data center environment. It routinely uses standard office equipment such as laptop computers, photocopiers, smartphones, ladders, forklifts, and scissor lifts. 

Physical Demands  

While performing the duties of this job, the employee is frequently required to sit, stand, walk, use hands, and lift up to 50 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