NLP PEOPLE
Piper Companies is seeking a AI/Machine Learning Ops Engineer to join a mission-critical forward team in Woodlawn, MD.
Responsibilities
Design and deploy scalable ML pipelines using Python and modern frameworks (e.g., TensorFlow, PyTorch, Transformers). Lead NLP and machine learning initiatives, applying statistical modeling and domain knowledge to solve complex business problems. Collaborate across teams, providing technical guidance and fostering a high-performing, motivated work environment. Utilize SQL/PostgreSQL and NoSQL databases (e.g., MongoDB) for data processing and model integration. Leverage cloud platforms and big data tools (AWS, Azure, Spark, Hadoop) to support AI-driven solutions. Qualifications
Master’s Degree + 5 years’ relevant experience OR Bachelor’s degree + 7 years of experience Minimum Public Trust clearance or eligibility is required. Expert proficiency in: Programming Languages: Python (Expert) Databases: PostgreSQL (Expert), MongoDB ML Frameworks & Libraries: TensorFlow, PyTorch, Transformers, Scikit-learn, XGBoost, Keras, Pandas NLP Techniques: Information Extraction, Semantic Parsing, Chunking/Tokenization, Pattern Recognition Model Types: BERT, CNN, RNN, LSTM, SVMs, k-NN, Regression, Classification, Ensemble Methods, Graphical Models, Clustering Tools & Technologies: Git, Tesseract, Regular Expressions Statistical Modeling: Classification, Feature Extraction, Sparse Data Analysis Cloud platforms: AWS, Azure, GCP Web service technologies: SOAP, WSDL, WS-Security NoSQL databases: DB2, Oracle, MySQL, HBase Big Data technologies: Hadoop, Spark, HDFS, MapReduce, YARN, Scala, PySpark XML and related technologies: XSD, XPath, XSLT Messaging systems: IBM MQ Series ebXML and other enterprise integration standards Compensation
Salary Range: $115,000-$125,000 depending on experience Full Benefits: Comprehensive benefits package (Healthcare, Dental, Vision, 401k, Paid Time Off, and Sick Leave where required by law) This job opens for applications on 9/29/25. Applications for this job will be accepted for at least 30 days from the posting date. Keywords: AI Engineer, Machine Learning Ops, MLOps, NLP, Natural Language Processing, Python, TensorFlow, PyTorch, Transformers, Scikit-learn, XGBoost, Keras, Pandas, CNN, RNN, LSTM, BERT, SVM, k-NN, Regression, Classification, Ensemble Methods, Graphical Models, Clustering, Feature Extraction, Sparse Data Analysis, Information Extraction, Semantic Parsing, Chunking, Tokenization, Pattern Recognition, Git, Tesseract, Regular Expressions, PostgreSQL, MongoDB, SQL, NoSQL, DB2, Oracle, MySQL, HBase, AWS, Azure, GCP, Spark, Hadoop, HDFS, MapReduce, YARN, Scala, PySpark, SOAP, WSDL, WS-Security, XML, XSD, XPath, XSLT, IBM MQ Series, ebXML, cloud platforms, big data, statistical modeling, scalable ML pipelines, model integration, public trust clearance, remote work, U.S. citizen, enterprise integration, mission-critical, cross-functional collaboration, technical guidance, high-performing teams.
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Design and deploy scalable ML pipelines using Python and modern frameworks (e.g., TensorFlow, PyTorch, Transformers). Lead NLP and machine learning initiatives, applying statistical modeling and domain knowledge to solve complex business problems. Collaborate across teams, providing technical guidance and fostering a high-performing, motivated work environment. Utilize SQL/PostgreSQL and NoSQL databases (e.g., MongoDB) for data processing and model integration. Leverage cloud platforms and big data tools (AWS, Azure, Spark, Hadoop) to support AI-driven solutions. Qualifications
Master’s Degree + 5 years’ relevant experience OR Bachelor’s degree + 7 years of experience Minimum Public Trust clearance or eligibility is required. Expert proficiency in: Programming Languages: Python (Expert) Databases: PostgreSQL (Expert), MongoDB ML Frameworks & Libraries: TensorFlow, PyTorch, Transformers, Scikit-learn, XGBoost, Keras, Pandas NLP Techniques: Information Extraction, Semantic Parsing, Chunking/Tokenization, Pattern Recognition Model Types: BERT, CNN, RNN, LSTM, SVMs, k-NN, Regression, Classification, Ensemble Methods, Graphical Models, Clustering Tools & Technologies: Git, Tesseract, Regular Expressions Statistical Modeling: Classification, Feature Extraction, Sparse Data Analysis Cloud platforms: AWS, Azure, GCP Web service technologies: SOAP, WSDL, WS-Security NoSQL databases: DB2, Oracle, MySQL, HBase Big Data technologies: Hadoop, Spark, HDFS, MapReduce, YARN, Scala, PySpark XML and related technologies: XSD, XPath, XSLT Messaging systems: IBM MQ Series ebXML and other enterprise integration standards Compensation
Salary Range: $115,000-$125,000 depending on experience Full Benefits: Comprehensive benefits package (Healthcare, Dental, Vision, 401k, Paid Time Off, and Sick Leave where required by law) This job opens for applications on 9/29/25. Applications for this job will be accepted for at least 30 days from the posting date. Keywords: AI Engineer, Machine Learning Ops, MLOps, NLP, Natural Language Processing, Python, TensorFlow, PyTorch, Transformers, Scikit-learn, XGBoost, Keras, Pandas, CNN, RNN, LSTM, BERT, SVM, k-NN, Regression, Classification, Ensemble Methods, Graphical Models, Clustering, Feature Extraction, Sparse Data Analysis, Information Extraction, Semantic Parsing, Chunking, Tokenization, Pattern Recognition, Git, Tesseract, Regular Expressions, PostgreSQL, MongoDB, SQL, NoSQL, DB2, Oracle, MySQL, HBase, AWS, Azure, GCP, Spark, Hadoop, HDFS, MapReduce, YARN, Scala, PySpark, SOAP, WSDL, WS-Security, XML, XSD, XPath, XSLT, IBM MQ Series, ebXML, cloud platforms, big data, statistical modeling, scalable ML pipelines, model integration, public trust clearance, remote work, U.S. citizen, enterprise integration, mission-critical, cross-functional collaboration, technical guidance, high-performing teams.
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