Will design and develop advanced machine learning and deep learning models using Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) to uncover insights from complex enterprise datasets. Work directly with Large Language Models (LLMs) such as GPT-3.5, Claude, Mistral, BERT, RoBERTa, and T5 to enable intelligent text summarization, classification, and information extraction. Implement Retrieval-Augmented Generation (RAG) pipelines and embedding workflows using LangChain, LlamaIndex, and vector databases (FAISS, Weaviate) to enhance model context and accuracy. Fine-tune foundation models and applying prompt engineering strategies to adapt LLMs for business applications. Develop data processing and transformation pipelines using PySpark, Spark SQL, and Databricks to prepare large-scale structured and unstructured datasets for analytics and model training. Perform exploratory data analysis (EDA), data profiling, and feature engineering to identify trends, correlations, and predictive variables. Design and operationalize end-to-end machine learning workflows, from data acquisition to deployment, ensuring scalability and performance. Build and monitor MLOps pipelines using MLflow, Airflow, Docker, and Kubernetes to automate model versioning, testing, and deployment. Leverage cloud platforms including AWS (SageMaker, Lambda, Redshift, S3) for distributed training, storage, and orchestration of AI workloads. Evaluate and optimize models using statistical validation techniques and metrics such as precision, recall, F1-score, and ROC-AUC. Integrate LLM-based solutions into enterprise applications via REST APIs and microservices, ensuring reliability and low-latency inference. Design and execute A/B testing frameworks to assess the impact of machine learning and NLP models on business KPIs. Visualize insights and model performance through interactive dashboards in Tableau or Power BI for business and technical stakeholders. Implement and maintain data governance, privacy, and ethical AI standards ensuring compliance with internal and regulatory frameworks. Develop and maintain model explainability tools and reports using SHAP, LIME, and other interpretability frameworks. Create reusable feature stores and metadata catalogs to streamline model reuse and experimentation. Document methodologies, data sources, and workflows in GitHub, Confluence, and JIRA for auditability and reproducibility. Research and integrate emerging tools and frameworks in machine learning, NLP, and LLMs to advance organizational AI capabilities.
Position requires up to 100% domestic travel. This position is for full-time, salaried (W-2), permanent employment.
Requirements:
Position requires a Master’s Degree or foreign equivalent in Information Technology, Data Science, Computer Science, or a related field.
Please reference Job Number 786926 when sending resumes. Please mail resumes to: HR, Beacon Hill Solutions Group, LLC, 20 Ashburton Place, 5th Floor, Boston, MA 02108.
California residents: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
If you would like to complete our voluntary self-identification form, please click here or copy and paste the following link into an open window in your browser: https://jobs.beaconhillstaffing.com/jobs/eeoc/
Completion of this form is voluntary and will not affect your opportunity for employment, or the terms or conditions of your employment. This form will be used for reporting purposes only and will be kept separate from all other records.
Beacon Hill offers a robust benefit package including, but not limited to, medical, dental, vision, and federal and state leave programs as required by applicable agency regulations to those that meet eligibility. Upon successfully being hired, details will be provided related to our benefit offerings.