Ml Engineer Jobs

About The Position

Requirements

• B.S. in Data Science, AI/ML, Computer Science, or related field
• 7+ years of experience, preferably as Data Engineer/Scientist, Machine Learning Engineer, or Software Development
• Experience developing data pipelines and normalizing data with canonical Python packages (e.g. NumPy, Pandas, Polars)
• Experience contributing within a team setting using version control (e.g. git, GitLab, Bitbucket)
• Active TS/SCI U.S. Government Security Clearance

Nice To Haves

• M.S. or PhD in Data Science, AI/ML, Computer Science, or related field
• Active TS/SCI U.S. Government Security Clearance with Polygraph
• Experience with Gitlab, DevSecOps utilizing test-driven development, containers, (e.g. Docker, Docker Compose), cloud services (e.g. AWS), tools for distributed computing (e.g. Spark, Pyspark)
• Experience leading an interdisciplinary team of researchers and software developers
• Experience with Large Language Models and experience identifying ways to incorporate them into new domains and applications
• Applying Transformer-based architectures to domains in other areas outside of Natural Language Processing (NLP) such as computer vision
• Natural Language Processing algorithms such as BERT
• Reinforcement learning and familiarity with Gymnasium Gym, OpenEnv, TorchRL, RLlib, and Stable Baselines
• Applying clustering algorithms and/or deep neural networks to real life problems
• Implementing tracking and pattern-of-life algorithms
• Experience with GenAI Ops techniques (e.g. LLM-as-a-judge) and frameworks (e.g. LangFuse, MLFlow, Arize Phoenix)
• Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
• Experience with Linux
• Familiarity with using AWS cloud computing resources such as EC2, S3, Lambda, Bedrock, etc.
• Experience with any of the following additional languages: Java, C++, Rust, Go, and/or C#
• Experience implementing algorithms on the GPU in Python or C++ using CUDA and other CUDA libraries
• Experience in application deployment, virtualization, and containerization (e.g. Podman, Docker, Kubernetes, Rancher)
• Experience shaping and writing proposals

Responsibilities

• Work within a multidisciplinary team consisting of both developers and researchers. The team's core focus is the implementation of ETL pipelines to support a variety of AI/ML and LLM solutions, which in turn address a broad range of customer challenges.
• Assemble large, complex sets of data to support AI/ML algorithm implementation
• Build required infrastructure for optimal extraction, transformation and loading of data from various data sources
• Curate and maintain data that is stored in support of metrics and evaluation
• Implement Artificial Intelligence/Machine Learning algorithms
• Identify, design, and implement internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes
• Use Agile methodologies to develop software

Benefits

• flexible time off benefit
• robust learning resources
• competitive compensation
• competitive mix of benefits options is designed to support and protect employees and their families
• comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits