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Junior Machine Learning Compiler Engineer Jobs in Maryland

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Showing results 21-40

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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Artificial Intelligence/Machine Learning Engineer

Wyetech

Annapolis Junction, MD

Full-time

Re-posted 2 hours ago


Job description

At Wyetech, you’ll be at the center of an award-winning corporate culture, breaking technological barriers and solving real-world problems for our federal government customers. We are committed to hiring the best of the best, and in return, we offer a world-class, truly unique employee experience that is rare within our industry.
 
The Artificial Intelligence/Machine Learning (AI/ML) Engineer designs, creates, tests, and productizes AI/ML algorithms to solve business challenges. The AI/ML models they create should be capable of learning and making predictions as defined by the business logic developed to meet customer requirements. The AI/ML Engineer should be proficient in all aspects of model architecture, data pipeline interaction, and metrics application, interpretation, and presentation. The AI/ML Engineer needs familiarity with foundational concepts of application development, infrastructure management, data engineering, and data governance. Through an understanding of training, retraining, deploying, scheduling, monitoring, and improving models through iterative user and system feedback, the AI/ML Engineer designs and creates scalable solutions for optimal performance. The AI/ML Engineer may be responsible for leading geographically diverse teams and will often serve as a primary POC for AI-related matters, so must have exceptional analytical, problem-solving and communication skills. Expert knowledge of multiple programming languages, e.g. Python, Java, C, R, a plus. 
 
Due to federal contract requirements, United States Citizenship and position appropriate security clearance is required. (e.g. Active TS/SCI security clearance with agency appropriate polygraph).
Capabilities
  • Select appropriate data sets
  • Perform statistical analysis
  • Run machine learning algorithms
  • Use results to improve models
  • Train and retrain systems when needed   
  • Experience in working with various ML libraries and packages
  • Run standard test and evaluation protocols
  • Provide system integration oversight
  • Oversee Test and evaluation of AI and ML algorithms through an iterative design process to meet verification and validation requirements
  • Research and implement a broad range of AI and ML algorithms and tools
  • Design or Select appropriate data and knowledge representation methods
  • Recognize software architecture, data modelling, and data structures
  • Transform and convert data science prototypes into scalable solutions
  • Verify data and model output quality
  • Identify differences in data distribution that affect model performance
Required Qualifications
  • TS/SCI with agency appropriate poly
  • Five (5) years experience in applied machine learning in programs and contracts of similar scope, type, and complexity is required.
  • A Master's or Ph.D. degree in advanced math, artificial intelligence, data science, computer science or deep learning from an accredited college or university.
  • 5 additional years of machine learning experience with a relevant Bachelor's degree may be substituted for a Master's degree.
  • Experience with standard machine language frameworks, e.g. Pytorch, TensorFlow. 
The Benefits Package
  • Wyetech believes in generously supporting employees as they prepare for retirement. The company automatically contributes 20% of each employee's gross compensation to a Simplified Employee Pension (SEP) IRA, with no requirement for employee matching. All contributions are fully vested from day one, ensuring immediate ownership of retirement funds. 
 
Additional benefits include:
  • Wyetech provides a generous PTO plan of up to 200 hours annually, aligned with applicable state leave regulations. Employees have the flexibility to adjust their PTO allocation at the start of each calendar year, ensuring it meets their evolving needs.
 
Full-time employees have the option to participate in a variety of voluntary benefit plans including:
  • A Choice of Medical Plan Options, some with Health Savings Account (HSA)
  • Vision and Dental
  • Life and AD&D Benefits
  • Short and Long-Term Disability
  • Hospital Indemnity, Accident, and Critical Illness Insurances
  • Optional Identity Theft and Legal Protection Services
Company Environment & Perks
  • Employee Referral Bonus Eligibility up to $10,000 
  • Mobility Among Wyetech-supported Contracts 
  • Various contract and work locations throughout Maryland, Virginia, Colorado, Texas, Utah, Alaska, Hawaii and OCONUS
  • Various team-building events throughout the year such as: monthly lunches, summer company picnic, and an annual holiday party. 
  • Employees receive two complementary branded clothing orders annually.
Pay Range: $ - $ per hour*
Hourly pay rates listed for this position serve as a general guideline and are not a guarantee of compensation. Compensation will vary dependent upon factors including but not limited to: Government contract rates; education; relevant prior work experience, knowledge, skills, and competencies; certifications, and geographic location. *Hourly pay rates reflect the pre-benefit gross wage amounts.
Wyetech, LLC is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. 
 
Affirmative Action Statement:
Wyetech, LLC is committed to the principles of affirmative action in all hiring and employment for minorities, women, individuals with disabilities, and protected veterans.
 
Accommodations:
Wyetech, LLC is committed to providing an inclusive and accessible hiring process. If you need any accommodations during the application or interview process, please contact Brittney Wood. at 844-WYETECH x727 or staffing@wyetech.com. We are happy to provide reasonable accommodations to ensure equal access to all candidates. 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.