Machine Learning Architect

Job Description

If you are an innovative, experienced, and motivated engineer who loves to pioneer new technology through research and development, BAE Systems has a unique career opportunity for you. We are seeking an exceptional Machine Learning Architect to champion advanced technology and create impact for our Independent Research and Development projects.

Advanced Solutions Engineering (ASE) at BAE Systems drives advanced research and development efforts using technologies such as cloud computing, machine learning, and cybersecurity to address our customers' most pressing problems in the domain of geospatial intelligence. We embrace change, anticipate evolving technologies, and collaborate with universities and research labs to develop engineering discriminators and acquire new business opportunities.

As a Machine Learning Architect, you will bring your experience and expertise to Independent Research and Development (IRAD) projects. You will promote machine learning integration across multiple programs. In this highly impactful role, you will influence the direction of the research, prototyping, and productization of new machine learning models. You will interface with cross-functional teams including engineering, business development, program management, and contracts to support new business captures and proposals. You will apply your creativity to innovate sophisticated algorithms and design novel solutions that enhance the end user experience and provide intelligent insight to processed data.

As a member of ASE, you will work across many US DoD and IC mission areas and interface with customers and senior leadership of applicable programs. BAE Systems has a long history of delivering innovative and advanced technical solutions for the United States DoD and Intelligence Communities. We are looking for an experienced Machine Learning Architect to revolutionize how data is stored, processed, discovered, and used to drive business intelligence.

Typical Education & Experience
Typically a Bachelor's Degree and 8 years work experience or equivalent experience

Required Skills and Education

-Hands-on experience with Machine Learning techniques, tools, and application to production software
- Excellent programming skills in Python, Java or C/C++
- Familiarity with various statistical packages such as R, Spark, MLlib, Mahout, etc.
- Ability to conduct independent research and translate ideas into production code or prototype
- Highly motivated with a knack of thinking outside the box
- Strong system design skills and experience with distributed systems
- Strong understanding of theoretical and practical aspects of various machine learning techniques such as classification, regression, clustering, etc.
- Ability to obtain a TS/SCI clearance

Preferred Skills and Education

-MS or Ph.D. in Computer Science, Data Science, or Analytics with a focus in Machine Learning
- Software development experience in Agile SW Development practices
- Recent experience working with DoD or Intelligence Community customers
- Active or recent TS/SC clearance

About BAE Systems Electronic Systems
BAE Systems is a premier global defense and security company with approximately 90,000 employees delivering a full range of products and services for air, land and naval forces, as well as advanced electronics, security, information technology solutions and customer support and services.
The Electronic Systems (ES) sector spans the commercial and defense electronics markets with a broad portfolio of mission-critical electronic systems, including flight and engine controls; electronic warfare and night vision systems; surveillance and reconnaissance sensors; secure networked communications equipment; geospatial imagery intelligence products and systems; mission management; and power-and energy-management systems. Headquartered in Nashua, New Hampshire, ES employs approximately 13,000 people globally, with engineering and manufacturing functions primarily in the United States, United Kingdom, and Israel. Equal Opportunity Employer/Females/Minorities/Veterans/Disabled/Sexual Orientation/Gender Identity/Gender Expression

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