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Senior Machine Learning Software Engineer Jobs in Alabama

IGNITE

MACHINE LEARNING ENGINEER

Huntsville, AL · On-site

... software components, ensuring that machine learning pipelines work within the overall product ... Programming proficiency in Python and extensive knowledge of ML frameworks, libraries data ...

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Senior Machine Learning Software Engineer information

What is the difference between Senior Machine Learning Software Engineer vs Data Scientist?

AspectSenior Machine Learning Software EngineerData Scientist
CredentialsBachelor's or Master's in CS, ML, or related; experience with ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, integrates algorithms into products, collaborates with engineering teamsAnalyzes data, builds statistical models, visualizes insights, collaborates with business teams
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, healthcare

While both roles involve working with data and algorithms, Senior Machine Learning Software Engineers focus on developing and deploying scalable ML models within software systems, whereas Data Scientists primarily analyze data to generate insights and inform business decisions.

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

A Senior Machine Learning Software Engineer requires deep expertise in machine learning algorithms, statistical analysis, and strong programming skills in languages like Python or Java, typically supported by a degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, scikit-learn, as well as experience with cloud platforms and version control systems, is standard. Exceptional problem-solving, leadership, and communication skills help drive project success and mentor junior engineers. These competencies are crucial for designing scalable ML solutions, ensuring code quality, and effectively collaborating within cross-functional teams.

What is a Senior Machine Learning Software Engineer?

A Senior Machine Learning Software Engineer is an experienced professional who designs, develops, and deploys machine learning models and systems to solve complex problems. They work closely with data scientists, engineers, and other stakeholders to build scalable and efficient solutions that leverage large data sets and advanced algorithms. Their responsibilities often include architecting ML pipelines, optimizing model performance, and mentoring junior team members. Typically, they have a strong background in computer science, programming, and applied mathematics, along with several years of hands-on experience in machine learning and software engineering.

What are some common challenges Senior Machine Learning Software Engineers face when deploying models to production?

Senior Machine Learning Software Engineers often encounter challenges such as ensuring model scalability, maintaining performance under real-world data conditions, and integrating models seamlessly with existing systems. Handling data drift and monitoring model predictions for accuracy over time are also critical responsibilities. Collaboration with data engineers, DevOps, and product teams is essential to address these challenges and ensure robust, reliable deployments.
What are the most commonly searched types of Machine Learning Software Engineer jobs in Alabama? The most popular types of Machine Learning Software Engineer jobs in Alabama are:
What are popular job titles related to Senior Machine Learning Software Engineer jobs in Alabama? For Senior Machine Learning Software Engineer jobs in Alabama, the most frequently searched job titles are:
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Senior Machine Learning Software Engineer jobs near you

Mid-level Machine Learning Engineer

Astrion

Huntsville, AL • On-site

Full-time

Re-posted 8 days ago

Job description

Overview
Machine Learning Engineer
JOB LOCATION: Huntsville, Al
JOB STATUS: Full-time
CLEARANCE: TS/SCI w CI/Poly
TRAVEL: As needed
Astrion seeking a Machine Learning Engineer to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government customer in Huntsville, Alabama.
This role will be responsible for delivering automation to key national security missions interacting with petabyte-scale data on supercomputing resources.
The ideal candidate will have a background in AI/ML model development and deployment and have experience in Python programming, handling SQL databases, and working in command line interfaces.
The team will work with technologies including:
  • Open source, commercial, and government software packages such as Docker, Python, Jupiter Notebooks, PostgreSQL, and other tools.
  • Leverage GitOps patterns and CI/CD with tools like GitLab and GitHub.

Work Environment
  • Working conditions are normal for an office environment.
  • Fast paced, deadline-oriented environment.
  • May require periods of non-traditional working hours including consecutive nights or weekends (if applicable).

REQUIRED QUALIFICATIONS / SKILLS
  • TS/SCI with CI Polygraph
  • Degree in Computer Science, Statistics, Mathematics, Physics or another quantitative field.
  • 1-3 years of experience working with ML frameworks
  • Programming proficiency in Python and extensive knowledge of ML frameworks, libraries data structures, and data modeling.
  • Solid understanding of the full ML development lifecycle.
  • Experience working with SQL and NoSQL databases.
  • Experience with both Linux and Windows operating systems.
  • Knowledge of CI/CD and Agile methodologies.
  • Understanding of software design and system integration.

PREFERRED QUALIFICATIONS / SKILLS
  • Experience with petabyte scale data sets
  • Experience with multi-INT analytics
  • Experience deploying, monitoring, and scaling models in production environments

RESPONSIBILITIES
  • Integrate ML systems with other software components, ensuring that machine learning pipelines work within the overall product architecture.
  • Manage the transition from prototype to production, including setting up model deployment pipelines and monitoring solutions.
  • Construct optimized data pipelines to feed ML models; run tests and experiments and document findings.
  • Monitor model performance post-deployment including managing model drift, rollback, and failure scenarios.
  • Write clean, testable, maintainable code in Python and other languages.

#CJ

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