Machine Learning Engineer

About the role

Machine Learning Engineer

HRL Laboratories leads the development of next generation intelligent systems for physical and information science. Our work creates breakthroughs in automotive, aerospace and defense. We deliver solutions that remove limitations and build competitive advantage for our customers. Critical missions benefit from our team's research, which transitions into real-world applications. HRL is a private company owned by Boeing and GM. We prioritize purpose over profit and advance the state of the art.

This role is within a research team focused on next generation intelligent systems. The position centers on machine learning, multimodal AI, cognitive state sensing, and cognitive modeling. You will create adaptive software prototypes for mission driven R&D programs. Your work will drive human-machine synergy, applied machine learning models, and complex systems analytics. You will design algorithms and mission-ready solutions that strengthen autonomous and human-guided decision making for national security and commercial use.

Location

Calabasas, CA

Key Responsibilities

You will own the lifecycle for intelligent systems, guiding research from raw data intake to deployed solutions. This role requires independent execution in fast paced research. You translate cognitive models and human machine interaction insights into working prototypes that decision makers can use immediately.

• Architect scalable data pipelines that transform neurophysiological signals, behavioral metrics, and sensor feeds into structured training sets.
• Design and tune transformer based models, applying prompt strategies and RAG to align LLM outputs with cognitive state variables and environmental context.
• Implement cognitive state estimation algorithms that turn raw measurements into reliable user models for adaptive decision support.
• Refine software interfaces into APIs and containerized services using Docker and Kubernetes to support reliable mission workflows.
• Champion explainability and trust measures derived from cognitive science, improving how human operators interact with autonomous tools.
• Synthesize research findings into proposals, publications, and customer briefings that clearly communicate methods and value.
• Run controlled experiments that validate model performance, documenting results for government program reviews and invention disclosures.
• Prepare and deliver demonstrations that showcase prototype capabilities to stakeholders and support outreach for national security initiatives.
• Coordinate with interdisciplinary teams, ensuring that algorithms, sensor hardware, and operational constraints stay aligned throughout development.
• Maintain curiosity driven exploration while adhering to strict timelines, testing protocols, and security standards in high stakes environments.

Required Qualifications

You must hold an MS or Ph.D. in applied math, cognitive science, or a related field that provides rigorous analytical training. You need 3-5 years of applied ML/AI experience, with a record of shipped models and scientific or engineering impact.

You should understand human machine interaction concepts, including cognitive architectures, neurophysiological sensing, and behavioral analytics. You must be skilled with LLMs and multimodal AI, using transformers, fine tuning, and RAG while integrating human state feedback. You have to build scalable software systems, writing clean APIs and managing containerized environments with Docker and Kubernetes.

You apply supervised and unsupervised learning techniques, including reinforcement learning, using PyTorch, TensorFlow, or JAX. You perform data analytics, executing feature engineering and statistical modeling directly in Python on complex, high dimensional inputs. You are a U.S. citizen able to obtain and maintain a U.S. Government Security Clearance.

You thrive in fast paced, exploratory research, communicating across disciplines with clarity and precision. You bring a curiosity driven mindset and a strong desire to solve intricate problems that affect national security and commercial markets.

Nice to have

Prior experience with government funded R&D programs such as DARPA, IARPA, or ARPA H.

Skills & Tools

Algorithms, Cognitive Modeling, Data Analytics, Docker, Human Machine Interaction, Kubernetes, Large Language Models, Machine Learning, LLMs, Multimodal AI, PyTorch, RAG, React.js, TensorFlow, Transformers.

Practical Notes

U.S. Citizenship is required for employment, and you must be able to obtain a U.S. Government Security Clearance. Standard work hours apply; this role is not eligible for remote work arrangements. Employment is regular full time.

We are an EEO/AA employer M/F/D/V. We maintain a drug free workplace and perform pre-employment substance abuse testing.

If you would like more information about Equal Employment Opportunity as an applicant under the law, please visit Employees & Job Applicants | U.S. Equal Employment Opportunity Commission at https://www.hrl.com/careers/equal-employment.

What you'll do

• Architect scalable data pipelines that transform neurophysiological signals, behavioral metrics, and sensor feeds into structured training sets.
• Design and tune transformer based models, applying prompt strategies and RAG to align LLM outputs with cognitive state variables and environmental context.
• Implement cognitive state estimation algorithms that turn raw measurements into reliable user models for adaptive decision support.
• Refine software interfaces into APIs and containerized services using Docker and Kubernetes to support reliable mission workflows.
• Champion explainability and trust measures derived from cognitive science, improving how human operators interact with autonomous tools.
• Synthesize research findings into proposals, publications, and customer briefings that clearly communicate methods and value.
• Run controlled experiments that validate model performance, documenting results for government program reviews and invention disclosures.
• Prepare and deliver demonstrations that showcase prototype capabilities to stakeholders and support outreach for national security initiatives.
• Coordinate with interdisciplinary teams, ensuring that algorithms, sensor hardware, and operational constraints stay aligned throughout development.
• Maintain curiosity driven exploration while adhering to strict timelines, testing protocols, and security standards in high stakes environments.

Requirements

• Hold an MS or Ph.D. in applied math, cognitive science, or a related field that provides rigorous analytical training.
• Bring 3-5 years of applied ML/AI experience, with a record of shipped models and scientific or engineering impact.
• Understand human machine interaction concepts, including cognitive architectures, neurophysiological sensing, and behavioral analytics.
• Demonstrate skill with LLMs and multimodal AI, using transformers, fine tuning, and RAG while integrating human state feedback.
• Build scalable software systems, writing clean APIs and managing containerized environments with Docker and Kubernetes.
• Apply supervised and unsupervised learning techniques, including reinforcement learning, using PyTorch, TensorFlow, or JAX.
• Perform data analytics, executing feature engineering and statistical modeling directly in Python on complex, high dimensional inputs.
• Be a U.S. citizen able to obtain and maintain a U.S. Government Security Clearance.
• Thrive in fast paced, exploratory research, communicating across disciplines with clarity and precision.
• Exhibit a curiosity driven mindset and a strong desire to solve intricate problems that affect national security and commercial markets.
• Prior experience with government funded R&D programs such as DARPA, IARPA, or ARPA H is preferred.