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Junior Machine Learning Compiler Engineer Jobs in Shirley, NY

Advancedtechsearch

Senior Data Scientist

Holtsville, NY · On-site

$145 - $150/hr

Design, develop, and deploy machine learning models for predictive analytics, classification ... Perform feature engineering, model evaluation, and optimization using structured and unstructured ...

Trueline

Junior Estimator

Bay Shore, NY · On-site

$80K - $100K/yr

... heavy civil expertise while learning directly from an experienced Senior Estimator and ... Prior construction estimating, takeoff, project engineering, or closely related heavy civil ...

New

Trueline

Junior Estimator

Bay Shore, NY · Hybrid

$80K - $100K/yr

... heavy civil expertise while learning directly from an experienced Senior Estimator and ... Prior construction estimating, takeoff, project engineering, or closely related heavy civil ...

New

Festo SE & Co. KG

AI Engineer Intern

Islandia, NY

Machine Learning projects * Prompt engineering * AI workflow automation * Preferred experience working with or integrating REST APIs . * Exposure to AI frameworks and tools, such as Azure AI Services

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All JobsMachine Learning Compiler Engineer JobsJunior Machine Learning Compiler Engineer JobsJunior Machine Learning Compiler Engineer Jobs in Shirley, NY

Junior Machine Learning Compiler Engineer information

See Shirley, NY salary details

$35.5K

$76K

$116K

How much do junior machine learning compiler engineer jobs pay per year?

As of Aug 13, 2026, the average yearly pay for junior machine learning compiler engineer in Shirley, NY is $76,043.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,400.00 and $84,700.00 per year, depending on experience, location, and employer.

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.

What cities near Shirley, NY are hiring for Junior Machine Learning Compiler Engineer jobs? Cities near Shirley, NY with the most Junior Machine Learning Compiler Engineer job openings:
Junior Machine Learning Compiler Engineer jobs near you
Infographic showing various Junior Machine Learning Compiler Engineer job openings in Shirley, NY as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 26% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $76,043 per year, or $36.6 per hour.

PostDoc - Machine Learning

Brookhaven National Laboratory

Upton, NY • On-site

Full-time

Re-posted 14 days ago

Job description

Job Summary:
Brookhaven National Laboratory is a multidisciplinary laboratory delivering discovery science and transformative technology. They are seeking a post-doctoral research associate in machine learning to conduct research in ML, multimodal foundation models, continuous learning, and agentic AI systems for autonomous scientific discovery.
Responsibilities:
• Conduct research in ML, multimodal foundation models, continuous learning, and agentic AI systems for various problems relating to autonomous scientific discovery.
• Work in interdisciplinary collaborations with subject matter experts on various aspects of scientific data generation and processing and methods evaluation.
• Formulate high-quality research ideas and directions in collaboration with mentors in the department.
• Communicate research progress, challenges, and achievements, and engage within and beyond the department on new potential collaborations.
Qualifications:
Required:
• Ph.D. in computer science or a related field (e.g., engineering, applied mathematics, statistics)
• Strong theoretical understanding and practical experience in machine learning, multimodal foundation models, continuous learning, and agentic AI techniques
• Demonstrated publication record in machine learning field
• Excellent programming and computer science skills
Preferred:
• Practical experience developing novel ML, multimodal foundation models, continuous learning systems, or agentic AI models.
• Experience with state-of-the-art multimodal foundation models and agentic AI frameworks
• Experience in large-scale deep learning systems, large multimodal foundation model training and/or finetuning, and continuous learning pipelines.
• Experience in multi-modality data analysis (e.g., image, video, text).
• Experience working in multidisciplinary collaborations.
Company:
Brookhaven National Laboratory is a multi-purpose research institution focused on questions in basic and applied science. Founded in 1947, the company is headquartered in Upton, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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