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Junior Machine Learning Compiler Engineer Jobs in Washington

Beyond SOF

Engineer, Machine Learning

Washington, DC

The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties: Develop and implement ...

Beyond SOF

Engineer, Machine Learning

Washington, DC · On-site

The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties: Develop and implement ...

Full Scope

Machine Learning Engineer

Reston, VA

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly Salary: Competitive We are seeking a highly skilled and motivated Machine Learning Engineer to join ...

Samprasoft

Machine Learning Engineer

Mclean, VA

GCP/AWS Machine Learning Engineer Freddie Mac iLab is currently looking for Machine Learning Engineers in its Innovation Labs - Tech Strategy team. In this position, you will be responsible for ...

ManTech

Machine Learning Engineer

Herndon, VA

The Machine Learning Engineer will leverage their strong technical background and knowledge to support highly scalable machine learning-based applications, including both pipelines and services ...

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Junior Machine Learning Compiler Engineer information

What are typical projects and responsibilities for a Junior Machine Learning Compiler Engineer in a collaborative team setting?

As a Junior Machine Learning Compiler Engineer, you can expect to work on projects that focus on optimizing machine learning models for performance and deployment across various hardware platforms. Typical responsibilities include assisting in developing and debugging compiler passes, implementing optimizations, and contributing to code reviews. You'll frequently collaborate with senior engineers, data scientists, and hardware specialists to ensure that models are efficiently translated and executed. This role offers valuable learning opportunities through hands-on coding, exposure to state-of-the-art ML frameworks, and regular team meetings for knowledge sharing and mentorship.

What does a Junior Machine Learning Compiler Engineer do?

A Junior Machine Learning Compiler Engineer helps design, develop, and optimize compilers for machine learning models. Their work involves translating high-level machine learning code into efficient low-level code that can run on various hardware platforms, such as CPUs, GPUs, or specialized AI chips. They often collaborate with software engineers and data scientists to ensure that machine learning workloads run efficiently and correctly. This role typically involves programming, debugging, and performance tuning, often using languages like C++, Python, and specialized frameworks.

What are the key skills and qualifications needed to thrive as a Junior Machine Learning Compiler Engineer, and why are they important?

To thrive as a Junior Machine Learning Compiler Engineer, you need a solid background in computer science fundamentals, programming (especially C++ and Python), and foundational knowledge of machine learning and compiler theory. Familiarity with frameworks and tools such as LLVM, TensorFlow, MLIR, and version control systems is typically required, along with a relevant bachelor’s or master’s degree. Strong problem-solving abilities, attention to detail, and effective teamwork and communication skills set standout candidates apart. These skills and qualities are crucial for efficiently optimizing machine learning models for various hardware targets and collaborating on innovative compiler solutions.

What is the difference between Junior Machine Learning Compiler Engineer vs Data Scientist?

AspectJunior Machine Learning Compiler EngineerData Scientist
Required CredentialsBachelor's in Computer Science, Software Engineering, or related field; knowledge of compiler design and ML frameworksBachelor's or higher in Data Science, Statistics, Computer Science, or related field; strong analytical skills
Work EnvironmentSoftware development teams, focusing on compiler optimization for ML modelsData analysis teams, focusing on data interpretation and model development
Employer & Industry UsageTech companies, AI startups, hardware firmsTech firms, finance, healthcare, research institutions

The Junior Machine Learning Compiler Engineer primarily focuses on developing and optimizing compilers for machine learning models, requiring programming and compiler knowledge. In contrast, a Data Scientist analyzes data, builds models, and provides insights. Both roles are essential in AI and tech industries but differ in technical focus and daily tasks.

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Junior Machine Learning Compiler Engineer jobs near you
Artificial Intelligence/Machine Learning Engineer, Junior

Artificial Intelligence/Machine Learning Engineer, Junior

EverWatch

Annapolis Junction, MD

$55.28 - $72.11/hr

Other

Posted 23 days ago

Job description

Job Title
Artificial Intelligence/Machine Learning Engineer, Junior
Overview
EverWatch is a government solutions company providing advanced defense, intelligence, and deployed support to our country's most critical missions. We are a full-service government solutions company. Harnessing the most advanced technology and solutions, we strengthen defenses and control environments to preserve continuity and ensure mission success.
EverWatch employees are focused on tackling the most difficult challenges of the US Government. We offer the best salaries and benefits packages in our industry - to identify and retain the top talent in support of our critical mission objectives.
Commitment to Non-Discrimination:
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.
Responsibilities
Cyber and intelligence analysts rely on multi-step workflows that are time-sensitive, detail-rich, and critical to national security. As an AI/ML Engineer at EverWatch Solutions, you will work directly with mission users to develop and deploy artificial intelligence and machine learning solutions that enhance operational workflows, improve data accessibility, and support rapid decision-making in secure environments.
You will collaborate with operators, analysts, software developers, and mission leadership to capture operational needs and translate them into effective AI-enabled capabilities. Your work may include developing LLM-powered workflows, agent-based automation, and other AI/ML solutions that streamline analytical tasks and improve mission effectiveness.
You will support the integration of AI capabilities into existing operational systems while ensuring solutions are reliable, scalable, and compliant with security and governance requirements in classified environments. Additionally, you will contribute to data pipeline development, model evaluation, workflow optimization, and operational testing to support production-ready AI solutions.
Join us. The world can't wait.
Qualifications
You Have:
  • 1-4 years of experience with Python for data analysis and machine learning tasks through academic, internship, or project-based work
  • Knowledge of machine learning concepts including supervised learning, model evaluation, and data preprocessing
  • Familiarity with standard data science libraries and development tools
  • Ability to think analytically, solve problems effectively, and learn quickly in a fast-paced, mission-oriented environment
  • Ability to collaborate within a team and communicate technical concepts clearly
  • TS/SCI clearance with a polygraph
  • Bachelor's degree in computer science, Data Science, Electrical Engineering, Mathematics, Statistics, or a related technical field or master's degree with limited experience
Nice If You Have:
  • Experience with academic coursework, thesis work, or capstone projects involving machine learning, natural language processing, or data science applications
  • Experience with version control tools such as Git and collaborative development environments
  • Knowledge of deep learning frameworks such as PyTorch or TensorFlow
  • Knowledge of large language models (LLMs) and generative AI concepts
  • Knowledge of cloud platforms such as AWS, Azure, or GCP
  • Knowledge of containerization technologies such as Docker or Kubernetes
  • Knowledge of agentic AI, retrieval-augmented generation (RAG), or other applied NLP techniques
  • Prior internship, co-op, research, or project experience supporting government, defense, or intelligence community environments

Clearance:
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance with a polygraph is required.
Compensation at EverWatch is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $55.28 to $72.11 per hour. The estimate displayed represents the typical compensation range for this position and is just one component of EverWatch's total compensation package for employees.
Clearance Level
TS/SCI CIP
Job Locations
US-MD-Annapolis Junction
Skills
AI/ML, LLM, API, Python

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