Lead ML Engineer

JOB DESCRIPTION

Title:

Lead ML Engineer

Belong. Connect. Grow. with KBR!

KBR’s Security Solutions team provides high-end engineering and advanced technology solutions to our customers in the intelligence and security communities. In this position, your work will have a profound impact on the country’s most critical role – protecting our security.

KBR is seeking a Lead ML Engineer to join our team onsite in El Segundo, CA, Colorado Springs, CO or remote.

KBR (formerly LinQuest) is the prime contractor on the MSEIT contract. By applying to this position, you are in consideration for KBR employment. However, you also have the option to be hired by one of our subcontractor teammates.

The MILSATCOM Systems Engineering, Integration, and Test (MSEIT) effort provides leading edge Systems Engineering & Integration (SE&I) for the US Space Force’s Space Systems Center (SSC). We support the Space Force’s acquisition of state-of-the-art satellite communications systems, providing global secure, survivable, and protected communications for our nation’s warfighters. We seek technical individuals who will thrive in a highly collaborative work environment of small teams, using the most modern tools and methodologies to tackle the challenges of integrating complex space and ground communications systems.

Why Join Us?

• Innovative Projects: KBR’s work is at the forefront of engineering, logistics, operations, science, program management, mission IT and cybersecurity solutions.
• Collaborative Environment: Be part of a dynamic team that thrives on collaboration and innovation, fostering a supportive and intellectually stimulating workplace.
• Impactful Work: Your contributions will be pivotal in designing and optimizing defense systems that ensure security and shape the future of space defense.

Key Responsibilities:

• Drive Cross-Functional Program Execution: Lead complex, mission-critical software or ML programs across engineering, operations, and stakeholder teams, ensuring delivery aligns with strategic business goals.
• Hybrid Project and Agile Management: Apply a hybrid of traditional PMP and Agile/Scrum methodologies to manage project timelines, risks, and deliverables using tools like JIRA, Confluence, and MS Planner.
• Stakeholder Engagement & Requirements Management: Define and manage requirements while translating complex technical needs into clear, strategic outcomes for both technical and non-technical stakeholders.
• Risk & Dependency Management: Identify, track, and mitigate risks across multiple concurrent workstreams, adjusting priorities dynamically to ensure timely delivery.
• Mentorship & Leadership: Mentor cross-functional teams, lead prioritization workshops, and foster collaboration in high-pressure environments.

Work Environment:

Location: On-site or remote

Travel Requirements: Minimal

Working Hours: Standard

Qualifications:

Required:

• Ability to obtain and maintain a Secret security clearance is required for this position

• Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field
• Demonstrated expertise in designing and deploying advanced machine learning systems in production environments
• 15+ years’ experience in software engineering, including at least 2 years focused on machine learning and natural processing (NLP)
• Strong proficiency in Python for data processing, model development, and automation
• Experience with LangChain and/or LlamaIndex for building LLM-powered applications
• Hands-on experience in prompt engineering and LLM optimization
• Skilled in integrating knowledge graphs into LLM contexts for enhanced reasoning and retrieval
• Experience fine-tuning and evaluating model outputs for quality, bias, explainability, and performance
• Demonstrated leadership and communication skills, with experience mentoring technical teams
• Experience with multi-modal models (text, image, audio)
• Familiarity with graph databases (Neo4j, ArangoDB) and semantic reasoning frameworks
• Experience building custom LLM evaluation pipelines for benchmarking performance
• Experience with edge deployment and optimization of LLMs for constrained environments

Desired:

• PhD in Machine Learning, NLP, or related technical field
• Experience deploying LLM-based applications in high-security or government environments
• Experience designing and implementing Retrieval-Augmented (RAG) pipelines

Basic Compensation:  $134,000 - $190,000 in California and $122,000-$173,000 in Colorado

The offered rate will be based on the selected candidate’s knowledge, skills, abilities and/or experience and in consideration of internal parity.

Ready to Make a Difference? If you’re excited about making a significant impact in the field of space defense and working on projects that matter, we encourage you to apply and join our team.

KBR Benefits  

KBR offers a selection of competitive lifestyle benefits which could include 401K plan with company match, medical, dental, vision, life insurance, AD&D, flexible spending account, , paid time off, or flexible work schedule. We support career advancement through professional training and development.

Belong, Connect and Grow at KBR

At KBR, we are passionate about our people and our Zero Harm culture.  These inform all that we do and are at the heart of our commitment to, and ongoing journey toward being a People First company.  That commitment is central to our team of team’s philosophy and fosters an environment where everyone can Belong, Connect and Grow. We Deliver – Together. 

KBR is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to , , , , , , gender or expression, , , veteran status, genetic information, union status and/or beliefs, or any other characteristic protected by federal, state, or local law.