AI/ML Engineer, Lead

Booz Allen Hamilton•McLean, VA

20h

About The Position

AI/ML Engineer, Lead The Opportunity: As an experienced engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct statistical analyses on business processes using ML techniques makes you an integral part of delivering a customer-focused solution. We need your technical knowledge and desire to problem-solve to support Army R&D work in the realm of cutting-edge AI technologies. As a machine learning engineer on our army enterprise AI/ML team, you’ll train, test, deploy, and maintain models that learn from data. In this role, you’ll lead the direction of critical solutions by applying best-fit ML algorithms and introducing leading-edge technologies. You’ll share your knowledge with a large community of machine learning engineers across the company and collaborate with AI/ML solution architects, intel analysts, cloud architects, data engineers, and data scientists to deliver world class solutions to real world problems in the threat landscape and analysis domain, process data and information at a massive scale, and perform A/B testing tasks on ML models and integrated cloud systems. Your skills and extensive technical expertise will guide clients as they navigate the landscape of ML algorithms, tools, and frameworks. Work with us to solve real-world challenges and define ML strategy for Army Enterprise clients. Join us. The world can’t wait.

Requirements

8+ years of experience with engineering code in an object-oriented language, such as Python, C, C++, Go, Rust, Java, or Haskell
4+ years of experience creating software for retrieving, parsing, and processing structured and unstructured data
3+ years of experience with implementing advanced data science, natural language processing or machine learning models
3+ years of experience coding Dataframes utilizing Pandas, Polars, or PySpark as well as understanding data formats, such as JSON, Parquet, Avro, or CSV
2+ years of experience designing, developing, operationalizing, and maintaining complex data science applications at enterprise scale
2+ years of experience in working with algorithms, machine learning models, or MLOps to produce analytical or visual products
Secret clearance
Bachelor's degree in computer science or computer engineering

Nice To Haves

10+ years of experience using Python, C, C++, Go, Rust, Java, or Haskell
5+ years of experience with a public cloud, including AWS, Microsoft Azure, or Google Cloud
5+ years of experience with Distributed data or computing tools, such as Spark, Databricks, Hadoop, Hive, HBase, Accumulo, AWS EMR, Nifi, Luigi, Dask, or Kafka
5+ years of experience with NoSQL databases such as Elasticsearch, Solr, MongoDB, or Cassandra
5+ years of experience with data warehousing and databases such as AWS Redshift, PostgreSQL, MySQL, Oracle, or Snowflake
2+ years of experience working in a team environment for git, GitLab, or GitHub
2+ years of experience with scaling data engineering or ETL/ELT across distributed computing clusters, such as Apache Nifi, Spark, Dask, Airflow, or Luigi
Master’s degree in data science, computer science, or ML engineering
AWS, Google, Data Analytics, Machine Learning Engineer, or Solutions Architect Certifications
ML engineering, cloud architecture, software engineering, web development, or data science Certifications

Responsibilities

Train, test, deploy, and maintain models that learn from data
Lead the direction of critical solutions by applying best-fit ML algorithms and introducing leading-edge technologies
Share your knowledge with a large community of machine learning engineers across the company
Collaborate with AI/ML solution architects, intel analysts, cloud architects, data engineers, and data scientists to deliver world class solutions to real world problems in the threat landscape and analysis domain, process data and information at a massive scale, and perform A/B testing tasks on ML models and integrated cloud systems
Guide clients as they navigate the landscape of ML algorithms, tools, and frameworks
Define ML strategy for Army Enterprise clients