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Senior Machine Learning Software Engineer Jobs in Alabama

They are currently seeking a driven Software Engineer to support the Army Logistics Engineering ... Machine Learning (ML) and Artificial Intelligence (AI) architectures and use cases in support of ...

Senior Software Developer

Huntsville, AL ยท On-site

$53.75 - $71/hr

Automate the training, testing, and deployment of machine learning models. * Implement and manage ... in software development, MLOps, DevOps, or related roles. * Proficiency in Python and experience ...

Senior Software Developer

Huntsville, AL ยท On-site

$53.75 - $71/hr

Automate the training, testing, and deployment of machine learning models. * Implement and manage ... in software development, MLOps, DevOps, or related roles. * Proficiency in Python and experience ...

Showing results 41-60

Senior Machine Learning Software Engineer information

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 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 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 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:

What cities in Alabama are hiring for Senior Machine Learning Software Engineer jobs?

Cities in Alabama with the most Senior Machine Learning Software Engineer job openings:

Machine Learning Engineer / Predictive Analyst

Vaco by Highspring

Birmingham, AL โ€ข On-site

Other

Dental, Vision, Retirement

Posted 13 days ago


Key responsibilities

  • Design, build, test, and deploy machine learning and predictive analytics models using large-scale structured and unstructured datasets

  • Develop forecasting and predictive modeling solutions supporting sales, marketing, and operational business initiatives

  • Partner directly with business stakeholders to translate ambiguous business requests into actionable data solutions


Job description

Machine Learning Engineer / Predictive Analytics Consultant
Preferred Locations: Birmingham, AL or Dallas, TX 
Position Overview
We are seeking a hands-on Machine Learning Engineer / Predictive Analytics Consultant to join an established machine learning team focused on scaling predictive analytics capabilities across the business. This role will support high-impact initiatives primarily focused on sales and marketing forecasting, predictive modeling, and business intelligence transformation efforts.
The organization has already built out a mature cloud and big data environment and is now focused on increasing delivery capacity, accelerating project timelines, and expanding the teamโ€™s ability to support growing business demand. This individual will help transition the business beyond traditional dashboarding and reporting into forward-looking predictive analytics and forecasting solutions.
This is a highly collaborative but autonomous role requiring someone who can operate with minimal guidance, solve complex business problems independently, and deliver practical machine learning solutions at enterprise scale.

Key Responsibilities
  • Design, build, test, and deploy machine learning and predictive analytics models using large-scale structured and unstructured datasets
  • Develop forecasting and predictive modeling solutions supporting sales, marketing, and operational business initiatives
  • Partner directly with business stakeholders to translate ambiguous business requests into actionable data solutions
  • Perform exploratory data analysis, feature engineering, model selection, validation, tuning, and performance optimization
  • Work with existing enterprise-scale cloud and big data environments to support scalable analytics initiatives
  • Help increase team throughput by accelerating project delivery and supporting a growing backlog of analytics requests
  • Collaborate with cross-functional teams including analytics, engineering, and business leadership
  • Communicate analytical findings and model outcomes clearly to both technical and non-technical stakeholders
  • Contribute to ongoing improvements in predictive analytics processes, scalability, and operational efficiency

Required Qualifications
  • 5+ years of experience in Machine Learning, Predictive Analytics, Data Science, or related data-focused roles
  • Strong hands-on experience with:
    • Python
    • SQL
    • Spark / PySpark  (Nice to have)
    • Snowflake (Nice to have)
  • Experience building machine learning and predictive models from the ground up
  • Experience working with large-scale datasets and distributed data processing environments
  • Strong understanding of statistical analysis, forecasting, predictive modeling, and machine learning methodologies
  • Experience operating within cloud-based analytics ecosystems (AWS, Azure, or GCP)
  • Proven ability to work independently with minimal direction
  • Strong analytical thinking and problem-solving skills
  • Ability to translate business problems into scalable technical solutions

Preferred Qualifications
  • Experience supporting sales and marketing analytics initiatives
  • Experience with forecasting and business performance prediction models
  • Experience working in enterprise-scale machine learning environments
  • Exposure to Databricks or similar modern data platforms
  • Experience communicating directly with business stakeholders and leadership teams

Ideal Candidate Profile
The ideal candidate is not someone who simply executes assigned tasks. We are looking for a proactive problem solver who can independently identify opportunities, work through ambiguity, and deliver practical machine learning solutions that drive measurable business value. This individual should be comfortable operating in a fast-paced environment with evolving priorities and growing demand for predictive analytics capabilities.
Determining compensation for this role (and others) at Vaco/Highspring depends upon a wide array of factors including but not limited to the individualโ€™s skill sets, experience and training, licensure and certifications, office location and other geographic considerations, as well as other business and organizational needs. With that said, as required by local law in geographies that require salary range disclosure, Vaco/Highspring notes the salary range for the role is noted in this job posting. The individual may also be eligible for discretionary bonuses, and can participate in medical, dental, and vision benefits as well as the companyโ€™s 401(k) retirement plan. Additional disclaimer: Unless otherwise noted in the job description, the position Vaco/Highspring is filing for is occupied. Please note, however, that Vaco/Highspring is regularly asked to provide talent to other organizations. By submitting to this position, you are agreeing to be included in our talent pool for future hiring for similarly qualified positions. Submissions to this position are subject to the use of AI to perform preliminary candidate screenings, focused on ensuring minimum job requirements noted in the position are satisfied. Further assessment of candidates beyond this initial phase within Vaco/Highspring will be otherwise assessed by recruiters and hiring managers. Vaco/Highspring does not have knowledge of the tools used by its clients in making final hiring decisions and cannot opine on their use of AI products.