# Holden Kjerland-Nicoletti

> Software Engineer @ Meta | Machine Learning, Software Development

Location: New York, New York, United States
Profile: https://flows.cv/holdenkjerlandnicoletti

I’m a software engineer focused on building and deploying machine learning systems that operate reliably at scale and deliver measurable impact.

Currently at Meta, I work on Ads machine learning, where I design and ship models that directly influence product performance and revenue. My work spans the full lifecycle of ML systems, including data pipelines, modeling, production deployment, experimentation, and monitoring. I’ve led projects that operate under real world constraints such as privacy limitations and noisy data while still driving significant business outcomes.

Prior to Meta, I built scalable backend systems and data pipelines using Python, Go, and distributed infrastructure. That experience gave me a strong foundation in system design and reliability, which I now apply to machine learning systems in production.

I’m particularly interested in the emerging space of generative AI and applied AI systems. I enjoy working at the intersection of deep technical engineering and real world use cases, especially roles that involve collaborating closely with users to translate powerful models into practical tools.

Technically, my background includes distributed systems, machine learning, and data infrastructure, with experience across Python, Go, Kubernetes, Spark, and large scale ML pipelines.

## Work Experience
### Software Engineer @ Meta
Jan 2024 – Present | New York, New York, United States
Ads Core ML

-Implementing and improving ML models that optimize ad delivery and drive measurable business impact
-Owning the full lifecycle of production ML systems — including system design, data pipeline development, deployment, validation, monitoring, and cost analysis.
-Integrating 1st-party behavioral signals to enhance user conversion prediction models and improve Ads ranking performance.
-Built statistical models to estimate conversions lost due to privacy constraints (e.g., ATT), improving compliance and preserving $100M+ in ad revenue.
-Collaborating cross-functionally with product managers, data scientists, and infra teams to scale ML solutions across Meta's Ads ecosystem.

### Software Engineer II @ VMware
Jan 2023 – Jan 2024 | Austin, Texas, United States
-Developed Python and GO microservices within Kubernetes to create API endpoints for business and data engineering teams, enabling seamless data integration and processing at scale.
-Engineered and optimized a highly scalable backend API leveraging GO and Redis, resulting in a 90% reduction in API response time and enabling seamless integration across applications throughout the organization.
-Led the design and implementation of end-to-end data pipelines, harmonizing data from various sources into HDFS, ensuring reliable and efficient data processing for analysis; reduced data integration time by 80% and enhanced data consistency across the organization.
-Spearheaded the creation of scalable applications that effectively presented customer experience data
-Engineered and deployed automation tools that significantly streamlined repetitive tasks within the team, boosting productivity and enabling team members to focus on higher-value activities.
-Received two promotions during tenure for outstanding performance and contributions to project success.

### Data Engineer @ VMware
Jan 2021 – Jan 2023 | Austin, Texas, United States

### Data Engineer Intern @ VMware
Jan 2020 – Jan 2021 | Austin, Texas, United States
-Building end to end data pipelines and performing analysis on data, for various projects within VMware. 
-Using technology such as Spark, Hive, and Sqoop to move data from different databases such as  MongoDB, PostgreSQL, and HANA and putting into a Hadoop Distributed File System.
-Writing programs to automate the data pipelines described.
-Creating data visualization dashboards with Tableau.
-Technologies used: HDFS, Spark, Kubernetes, Hive, MongoDB, Kafka, Tableau, GO, Python, Sqoop.

### Undergraduate Research Assistant @ The Cooperative Human-Robot Intelligence Lab (COHRINT)
Jan 2019 – Jan 2020 | Boulder, CO
-Machine learning research lab focused on unmanned robots/vehicles, and their interactions with humans.
-Implemented target-searching strategies for autonomous robots by integrating Bayesian Loops and Gaussian Mixtures with human feedback
-Created a simulation environment within Unreal Engine 4, using ROS (Robot Operating System), to facilitate the testing and validation of autonomous drone searching algorithms. This innovation provided a controlled and immersive platform for algorithm refinement and optimization


## Education
### Master's degree in Computer Software Engineering
The University of Texas at Austin

### Bachelor of Science - BS in Computer Science and Applied Mathematics
University of Colorado Boulder


## Contact & Social
- LinkedIn: https://linkedin.com/in/holden-kjerland-nicoletti

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Source: https://flows.cv/holdenkjerlandnicoletti
JSON Resume: https://flows.cv/holdenkjerlandnicoletti/resume.json
Last updated: 2026-04-05