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Principal Machine Learning Engineer Jobs (NOW HIRING)

We are hiring a Principal Machine Learning Engineer to serve as the technical lead for our GenAI Services area. This is not a model-training or research role -- it is the senior-most hands-on ...

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Principal Machine Learning Engineer Employer: FactSet Research Systems Inc. Location: FactSet Research Systems Inc. , 45 Glover Avenue, 7th Floor, Norwalk, CT 06850. Remote Position: This position ...

POS-22209 Principal Machine Learning Engineer HubSpot is an all-in-one marketing, sales, and service software platform that helps businesses grow and succeed. With a user-friendly interface and ...

AI Senior Principal Machine Learning Engineer Experience : 12 to 18 years Skills : Python/Java, Cloud, PyTorch, CUDA, MapReduce, Spark, Flink, Kafka, PySpark, SageMaker About the position Are you ...

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Principal Machine Learning Engineer information

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$74K

$147.2K

$212.5K

How much do principal machine learning engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for principal machine learning engineer in the United States is $147,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What does a principal machine learning engineer do?

A Principal Machine Learning Engineer leads the design, development, and deployment of machine learning models and systems. They set technical strategy, mentor engineers, and collaborate with cross-functional teams to solve complex AI challenges. Their role often includes researching new algorithms, optimizing model performance, and ensuring scalability in production environments. Additionally, they work closely with data scientists, software engineers, and product managers to align ML initiatives with business objectives.

What skills and qualifications are needed to thrive as a principal machine learning engineer?

To thrive as a Principal Machine Learning Engineer, you need advanced expertise in machine learning algorithms, statistical analysis, software engineering, and a strong background in computer science or related fields, often supported by a master's or PhD degree. Familiarity with tools such as Python, TensorFlow, PyTorch, cloud platforms (AWS, GCP, Azure), and relevant certifications strengthens technical capability. Leadership, strategic thinking, effective communication, and mentorship are vital soft skills for guiding teams and collaborating across departments. These competencies are essential for driving innovation, ensuring technical excellence, and influencing organizational AI initiatives.

What types of projects and responsibilities can a principal machine learning engineer typically expect?

Principal Machine Learning Engineers are often tasked with leading the design, development, and deployment of large-scale machine learning models and systems that address key business challenges. In this role, you will collaborate closely with data scientists, engineers, and product managers to define project requirements, architect solutions, and ensure high-quality delivery. You may also guide research initiatives, oversee code and model reviews, and mentor junior engineers, helping to shape the technical direction of the team. Typical responsibilities can range from prototyping and optimizing algorithms to ensuring models are scalable, reliable, and aligned with organizational goals.

Is a principal machine learning engineer a high paying job?

A principal machine learning engineer is typically a high-level role with a competitive salary that reflects advanced expertise in machine learning, data science, and software engineering. Salaries often vary based on industry, location, and company size but generally exceed those of mid-level roles due to the experience and leadership responsibilities involved.
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Infographic showing various Principal Machine Learning Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $147,220 per year, or $70.8 per hour.

Principal Machine Learning Engineer

1000 Micron Technology, Inc.

Boise, ID โ€ข On-site

Full-time

Medical, Dental, Vision, PTO

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. The Smart Manufacturing and AI team at Micron Technology is looking for an ambitiousMachine LearningEngineer. Are you curious, high velocity, and ready to solve complex problems? Do you dream in data science and machine learning models? If so, we want you to join us! Our mission is to enabletodeliver industry-winning machine learning solutions to power Micron's dominance in the highlycompetitivememory solutions market! As a Principal Machine Learning Engineer, willhave experiencein a variety of dataand cloudtechnologies and have extensive practice modeling data, querying, anddeployingscalable pipelinestoexecute machine learning models. You will collaborate with Data Scientists,MLEngineers, DataEngineers, andexpert userstobuild and deployscalableAI/ML solutions that drive value and insight fromMicron'smanufacturing processes and systems. Responsibilities Design, build, and continuously refine ML models to address business challenges and enhance product capabilities. Analyze large datasets to uncover patterns, trends, and insights that inform and improve machine learning models. Stay ahead of advancements in AI/ML and integrate emerging techniques into the MLOps lifecycle. Build and maintain robust, scalable data pipelines and infrastructure to support model training and deployment. Collaborate on data preprocessing and feature engineering to improve input data quality and model performance. Design and optimize data architectures across cloud platforms (Snowflake, GCP, Azure) for AI/ML use cases. Develop custom applications and implement CI/CD pipelines to support efficient ML solution deployment. Deploy, evaluate, and monitor models in production, balancing performance with cost efficiency and enabling continuous improvement. Partner with Product and Engineering teams to define and implement Generative AI integration strategies and roadmaps. Communicate insights and collaborate multi-functionally, translating complex analytics into actionable recommendations for diverse collaborators. Drive the technical vision and lead end-to-end execution of complex, multi-functional AI/ML projects. Mentor and coach developing and senior team members, elevating the overall technical competence of the engineering team. Embrace and champion AI-assisted software development such as Opencode, Copilot; while strictly managing and auditing AI agents to ensure production quality code that is reliable, secure and high quality. Minimum Qualifications Master's or PhD degree in Computer Science, Machine Learning, Data Science, Statistics, or a field closely related to AI and Machine Learning with 8+ years (or PhD with 5+ years) experience building end-to-end ML systems on cloud platforms, automating model training, testing, and deployment. Strong experience with ML frameworks (scikit-learn, TensorFlow, PyTorch) and core techniques including regression, classification, deep learning, reinforcement learning, and generative AI. Proficient in Python or Java, with experience developing APIs and event-driven pipelines using Kafka, Pub/Sub, or similar messaging systems. Skilled in scalable data engineering, including ETL/ELT pipelines (Kubeflow, Airflow, Dataflow), SQL, and data architecture design. Handsโ€on experience with cloud and DevOps tools (GCP, AWS, Azure, Docker, Kubernetes), combined with strong analytical, communication, and collaboration skills. Proven track record of technical leadership, including leading ML project delivery and mentoring engineering teams. Preferred Qualifications Strong foundation in machine learning and deep learning, with solid grounding in probability and statistics. Proven ability to productionize data science prototypes into scalable, real-world solutions. Advanced experience using and managing GenAI coding assistants, with a strong ability to peer-review and rigorously test AI-generated code logic. Handsโ€on experience building Generative AI solutions and intelligent agents (ADK, LangChain/LangGraph, CrewAI, DsPy, Semantic Kernel). Expertise in semantic search and retrieval systems, including RAG, GraphRAG, NLP, prompt engineering, and LLM fineโ€tuning/evaluation. Experience with end-to-end data and engineering workflows: ETL pipelines, big data processing, databases (BigQuery, Snowflake, MSSQL, PostgreSQL), and CI/CD tools (Git, Docker, Kubernetes, Jenkins) and MLOps/CE platforms (MLflow, Kubeflow, Vertex AI, SageMaker, TFX). Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time-off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on micron.com/careers/benefits. Micron is dedicated to your personal wellbeing and professional growth. Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws. #J-18808-Ljbffr