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AI/ML Engineer specializing in end-to-end AI pipeline development—from data collection to real-time predictions—with a strong focus on NLP, deep learning, and supervised machine learning. Experienced in productionizing and monitoring models in cloud-native environments to reduce latency and improve time-to-market. Skilled at translating business needs into actionable technical solutions, partnering with cross-functional teams, and advancing AI research for real-time decision-making in healthcare and analytics-driven environments. Known for mentoring engineers and implementing robust MLOps, orchestration, and security/compliance-aware deployments.…AI/ML Engineer specializing in end-to-end AI pipeline development—from data collection to real-time predictions—with a strong focus on NLP, deep learning, and supervised machine learning. Experienced in productionizing and monitoring models in cloud-native environments to reduce latency and improve time-to-market. Skilled at translating business needs into actionable technical solutions, partnering with cross-functional teams, and advancing AI research for real-time decision-making in healthcare and analytics-driven environments. Known for mentoring engineers and implementing robust MLOps, orchestration, and security/compliance-aware deployments.

Zacch Williams

AI Engineer, Data Engineer, Software Engineer, +2

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AI/ML Engineer specializing in end-to-end AI pipeline development—from data collection to real-time predictions—with a strong focus on NLP, deep learning, and supervised machine learning. Experienced in productionizing and monitoring models in cloud-native environments to reduce latency and improve time-to-market. Skilled at translating business needs into actionable technical solutions, partnering with cross-functional teams, and advancing AI research for real-time decision-making in healthcare and analytics-driven environments. Known for mentoring engineers and implementing robust MLOps, orchestration, and security/compliance-aware deployments.…AI/ML Engineer specializing in end-to-end AI pipeline development—from data collection to real-time predictions—with a strong focus on NLP, deep learning, and supervised machine learning. Experienced in productionizing and monitoring models in cloud-native environments to reduce latency and improve time-to-market. Skilled at translating business needs into actionable technical solutions, partnering with cross-functional teams, and advancing AI research for real-time decision-making in healthcare and analytics-driven environments. Known for mentoring engineers and implementing robust MLOps, orchestration, and security/compliance-aware deployments.

Available to hire

AI/ML Engineer specializing in end-to-end AI pipeline development—from data collection to real-time predictions—with a strong focus on NLP, deep learning, and supervised machine learning. Experienced in productionizing and monitoring models in cloud-native environments to reduce latency and improve time-to-market.

Skilled at translating business needs into actionable technical solutions, partnering with cross-functional teams, and advancing AI research for real-time decision-making in healthcare and analytics-driven environments. Known for mentoring engineers and implementing robust MLOps, orchestration, and security/compliance-aware deployments.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Beginner

Language

English

Advanced

Javanese

Advanced

Aragonese

Intermediate

Bashkir

Intermediate

Work Experience

Advisor/AI Engineer at IBM

September 1, 2023 - June 1, 2026

Spearheaded development and deployment of Large Language Models (LLMs) to build AI-driven solutions addressing complex business challenges, emphasizing real-time data processing, microservices architecture, and cloud scalability on AWS. Led enterprise integrations for advanced AI models, improving performance, scalability, and security while reducing latency and improving operational efficiency. Drove model deployment and monitoring strategies using orchestration tools such as Airflow, Dagster, and Prefect to automate and manage complex ML pipelines. Implemented automation for actionable AI-driven business intelligence and continuous model refinement via feedback loops and real-world data. Managed model versioning and deployment pipelines using GitHub Actions, and mentored junior engineers on best practices for ML development, deployment, and monitoring.

Advisor y AI Engineer at IBM

September 1, 2023 - May 1, 2026

Spearheaded development and deployment of Large Language Models (LLMs) for AI-driven enterprise solutions, focusing on real-time data processing, microservices architecture, and AWS cloud scalability. Led integration of advanced AI models into production environments, improving performance, scalability, and security while reducing latency and time-to-market. Owned model deployment and monitoring strategies with workflow orchestration tools (Airflow, Dagster, Prefect) to manage automated ML pipelines. Applied continuous improvement through feedback loops and real-world data to refine models for ongoing business needs. Managed model versioning and deployment pipelines using GitHub Actions. Collaborated with cross-functional teams (data scientists, engineers, business leaders) to align AI outcomes with organizational goals, compliance, and regulatory requirements. Mentored junior engineers and guided best practices for ML development, deployment, and monitoring.

Machine Learning Engineer II at Memorial Sloan Kettering Cancer Center

May 1, 2022 - September 1, 2023

Led AI/ML research initiatives with clinicians and researchers to build AI-powered tools that supported cancer care and improved patient outcomes. Developed and deployed real-time predictive models enabling clinicians to make faster, data-driven decisions regarding treatment effectiveness. Designed and implemented clinical discovery platforms integrating predictive analytics for personalized treatment strategies and improved diagnostic accuracy. Built large-scale data processing workflows with HIPAA-compliant handling for real-time data integration. Developed computer vision models using OpenCV, TensorFlow, and PyTorch for healthcare image-based analysis. Contributed to a predictive analytics platform that improved clinical trial efficiency by identifying promising treatment options sooner, and supported clinical adoption by training staff to interpret model insights and integrate them into decision workflows.

Senior Data Scientist at Global Algorithmic Institute

March 1, 2021 - February 1, 2022

Designed and deployed deep learning models enabling remote patient monitoring with real-time tracking of vitals and behavior. Developed algorithms for advanced data representations in high-dimensional spaces to improve predictive power for healthcare models. Worked with healthcare professionals to integrate machine learning into decision-making and deployed models at scale for production inference. Built and maintained real-time data pipelines using Apache Kafka to ingest, process, and stream high-volume data for ML and analytics. Integrated Kafka event streams with Python and Spark for near real-time inference and reporting, and designed scalable streaming workflows with Kafka producers/consumers to improve reliability and reduce latency.

Senior Data Scientist at Algorithmic Intuition

March 1, 2021 - February 1, 2022

Designed and deployed deep learning models for remote patient monitoring to enable real-time tracking of patient vitals and behavior. Developed algorithms for advanced data representations in high-dimensional spaces to improve predictive power of healthcare models. Worked closely with healthcare professionals to integrate machine learning into clinical decision-making and improve operational efficiency. Deployed models at scale with real-time inference in production to support patient care workflows.

Data Scientist III at EMployers (as listed)

October 1, 2018 - March 1, 2021

Built and deployed machine learning models using Python, scikit-learn, TensorFlow, and XGBoost to improve prediction accuracy, automate decision-making, and support business growth. Designed scalable ETL and real-time streaming pipelines using SQL, Spark, Pandas, AWS, and Apache Kafka to deliver reliable data for analytics and near real-time decision-making. Created dashboards and visualizations in Tableau, Power BI, and Python to communicate insights. Collaborated with engineering and product teams on experiments, model evaluation, and production-ready AI/predictive analytics solutions. Coordinated with data engineering on event-driven architectures and fault-tolerant data movement across analytics platforms. Monitored and optimized Kafka flows, partitioning strategies, and consumer performance for large-scale production workloads.

Data Scientist at Audatex (a Solera company)

February 1, 2018 - October 1, 2018

Led AI initiatives to optimize business operations, leveraging NLP to enhance customer experience and engagement. Built ML models to automate decision-making and reduce operational costs. Developed predictive analytics solutions to improve customer engagement and retention. Used TensorFlow, PyTorch, Apache Kafka, and AWS to deploy ML models processing large-scale data in near real-time. Implemented Kafka-based streaming pipelines for high-volume event data, optimized producer/consumer workflows with Python and Spark to improve throughput, processing reliability, and insight generation. Contributed to internal product enhancements across NLP and computer vision, developed predictive models for real-time analysis, and supported end-to-end data-driven solutions including data extraction/processing and integration with client systems.

Data Scientist at Atos

April 1, 2017 - February 1, 2018

Collaborated with senior data scientists, big data engineers, and solution architects to implement end-to-end data-driven solutions in large-scale analytics environments. Developed machine learning and deep learning models for NLP, computer vision, and unsupervised pattern recognition. Supported enterprise data ingestion using Apache NiFi/MiNiFi and Hortonworks Data Platform to collect, transform, and route high-volume multi-source data. Built distributed processing workflows using Apache Spark, Python, and Hadoop-based platforms. Developed predictive/classification models using TensorFlow, scikit-learn, Python, R, and MATLAB to support business analytics solutions. Worked with the ELK stack (ElasticSearch/Logstash/Kibana) for indexing/search/monitoring of structured and unstructured data. Integrated ML components with Java/Spring applications and automated data processing/operational workflows using Linux/Bash.

Data Scientist at Employers, Audatex, a Solera company, Atos

December 1, 2016 - March 1, 2021

Spearheaded AI initiatives to optimize business operations using NLP to improve customer experience and engagement. Built ML models to automate decision-making and reduce operational costs, and developed predictive analytics for customer engagement and retention. Developed and deployed models using TensorFlow, PyTorch, and AWS for real-time processing and large-scale efficiency. Led Solera Analytics data science initiatives for NLP and computer vision, built end-to-end solutions from ingestion to deployment, and collaborated with big data engineers to integrate solutions into client systems.

Data Scientist at Employers: Audatex (A Solera company), Atos

December 1, 2016 - March 1, 2021

Spearheaded AI initiatives to optimize business operations by leveraging Natural Language Processing (NLP) to enhance customer experience and engagement. Built ML models to automate decision-making and reduce operational costs, improving service delivery. Led development of predictive analytics solutions delivering actionable insights for customer engagement and retention. Deployed ML models using TensorFlow, PyTorch, and AWS for efficient large-scale and real-time processing. Led data science efforts across Solera Analytics, focusing on NLP and computer vision for internal products, supporting end-to-end data-driven solutions from ingestion to deployment, and collaborated with big data engineers to integrate AI into client systems to improve downstream processing and decision-making.

Data Scientist at Employers: Audatex, a Solera company, Atos

December 1, 2016 - March 1, 2021

Spearheaded AI initiatives to optimize business operations using NLP to enhance customer experience and engagement. Built machine learning models to automate decision-making, reduce operational costs, and improve service delivery. Led predictive analytics efforts providing actionable insights for customer engagement and retention. Deployed models at scale using TensorFlow, PyTorch, and AWS for efficient processing and real-time analytics. Directed data science initiatives for Solera Analytics focused on NLP and computer vision to enhance internal products and services. Developed end-to-end data-driven solutions from ingestion through deployment, including pattern recognition in unstructured data and integration of AI solutions into client systems with big data engineering teams.

Software Developer at IBM

June 1, 2015 - December 1, 2016

Worked on development and deployment of web, mobile, and desktop applications as part of a global team. Integrated AI models into client-facing applications to enhance functionality and increase client satisfaction. Contributed to client-driven projects by applying programming and project management skills to deliver high-quality results on schedule.

Education

Master of Science, Electrical Engineering Technologies at Louisiana Tech University

January 1, 2016 - January 1, 2018

Bachelor of Science, Electrical Engineering Technologies at Louisiana Tech University

January 1, 2010 - January 1, 2015

Master of Science, Electrical Engineering Technologies at Louisiana Tech University

January 1, 2016 - January 1, 2018

Bachelor of Science, Electrical Engineering Technologies at Louisiana Tech University

January 1, 2010 - January 1, 2015

Master of Science, Electrical Engineering Technologies at Louisiana Tech University

January 1, 2016 - December 31, 2018

Bachelor of Science, Electrical Engineering Technologies at Louisiana Tech University

January 1, 2010 - December 31, 2015

Master of Science, Electrical Engineering Technologies at Louisiana Tech University

January 1, 2016 - January 1, 2018

Bachelor of Science, Electrical Engineering Technologies at Louisiana Tech University

January 1, 2010 - January 1, 2015

Master of Science, Electrical Engineering Technologies at Louisiana Tech University

January 1, 2016 - January 1, 2018

Bachelor of Science, Electrical Engineering Technologies at Louisiana Tech University

January 1, 2010 - January 1, 2015

Bachelor of Science, Electrical Engineering Technologies at Louisiana Tech University

January 1, 2010 - January 1, 2015