Based in Bethesda, MD with remote options, Lockheed Martin provides a comprehensive benefits package and a culture that emphasizes collaboration, growth, and innovative problem solving. This early-career A/AI Machine Learning Engineer role centers on leading the AI Consulting portfolio and delivering AI solutions across the enterprise, blending software development, AI/ML expertise, and business sense.
Benefits
- Medical
- Dental
- Vision
- Life Insurance
- Short-Term Disability
- Long-Term Disability
- 401(k) match
- Flexible Spending Accounts
- EAP
- Education Assistance
- Parental Leave
- Paid time off
- Holidays
Technologies
Responsibilities
- Lead the AI Consulting portfolio.
- Oversee the development and deployment of AI solutions that drive business value and foster innovation across the enterprise.
Requirements
- Bachelor’s Degree in Engineering or Computer Science from an accredited college in a related discipline, or equivalent experience.
- Experience building machine learning models through work, projects, or coursework.
- Experience developing software with engineering best practices, specifically using Python.
- Strong problem-solving skills, business acumen, and demonstrated excellent oral and written communication skills.
- US citizenship.
- 4+ years of related experience.
Remote work and location
This is a full-time remote telework role. The selected candidate may travel to a Lockheed Martin office for periodic meetings. Relocation is not available for this position.
Work schedules
- 4x10 hour days, three days off per week
- Lockheed Martin supports alternate schedules offering flexibility beyond the standard 40-hour week
Pay and location details
The base salary range for this position in most major metropolitan areas of California, Massachusetts, and New York is USD 84,200 to 145,935 per year. For states not listed above, the final range reflects the candidate’s work location. In some contexts, a secondary range of USD 73,200 to 129,030 applies for other states. These figures are general guidelines and may be influenced by factors such as scope, responsibilities, experience, education, and key skills.
