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Machine Learning Engineer Jobs in Birmingham, AL

Pwc

NGA AI Engineer Senior Manager

Birmingham, AL

$91K - $321K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Maximus

AI/ML Software Developer

Birmingham, AL · Remote

Prepares and structures data for machine learning pipelines, feature engineering, and model lifecycle management * Implements model monitoring, performance validation, traceability, and ...

Maximus

AI/ML Software Developer

Birmingham, AL · On-site

Prepares and structures data for machine learning pipelines, feature engineering, and model lifecycle management * Implements model monitoring, performance validation, traceability, and ...

Pwc

US Tech - AI Engineering Manager

Birmingham, AL · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Tocaro Blue

Senior Software Engineer

Birmingham, AL · On-site

$120K - $145K/yr

... machine learning models to deliver real-time situational awareness. We are looking for a Senior ... Software Engineer whose primary role will be to architect and develop software applications ...

Apply Early

Tocaro Blue

Senior Software Engineer

Birmingham, AL · On-site

$120K - $145K/yr

... machine learning models to deliver real-time situational awareness. We are looking for a Senior ... Software Engineer whose primary role will be to architect and develop software applications ...

4pconsultinginc

Data Visualization Engineer I

Birmingham, AL · On-site

$107K - $128K/yr

Machine learning techniques * Data mining * Statistical analysis * Translate business requirements into technical data solutions Data Engineering & Integration Support * Work with ETL processes and ...

Apply Early

EBSCO Industries Inc

GIS Data Engineer

Birmingham, AL · Remote

... for machine learning and data science workflows. This role helps ensure geospatial data is ... Support the Senior GIS Developer in building and maintaining GIS data workflows using open-source ...

EBSCO Industries, Inc.

GIS Data Engineer

Birmingham, AL · On-site

... for machine learning and data science workflows. This role helps ensure geospatial data is ... Support the Senior GIS Developer in building and maintaining GIS data workflows using open-source ...

4pconsultinginc

Data Engineer III

Birmingham, AL · On-site

$107K - $128K/yr

Prepare data pipelines to enable machine learning workflows DevOps & Modern Engineering Practices * Implement CI/CD pipelines for data engineering deployments * Work within Agile development ...

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Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Birmingham, AL

Machine Learning Engineer information

See Birmingham, AL salary details

$29.5K

$120.7K

$181.3K

How much do machine learning engineer jobs pay per year?

As of Jul 5, 2026, the average yearly pay for machine learning engineer in Birmingham, AL is $120,681.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,100.00 and $145,300.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Birmingham, AL? The most popular types of Machine Learning Engineer jobs in Birmingham, AL are:
What are popular job titles related to Machine Learning Engineer jobs in Birmingham, AL? For Machine Learning Engineer jobs in Birmingham, AL, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Birmingham, AL look for? The top searched job categories for Machine Learning Engineer jobs in Birmingham, AL are:
What cities near Birmingham, AL are hiring for Machine Learning Engineer jobs? Cities near Birmingham, AL with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Birmingham, AL as of June 2026, with employment types broken down into 1% As Needed, 97% Full Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $120,681 per year, or $58 per hour.

Data Scientist (Level III)

4pconsultinginc

Birmingham, AL • On-site

Contractor

Posted 29 days ago

Job description

Position:  Senior Data Scientist (Level III)

Location:  3535 Colonnade Parkway, Birmingham AL 35243
Duration:  6 Months

Client:       Southern Nuclear

Position Overview

We are seeking a highly experienced Senior Data Scientist (Level III) to lead advanced analytics and machine learning initiatives that drive strategic business decisions.

This role requires deep expertise in statistical modeling, predictive analytics, and big data technologies, along with strong leadership capabilities. The ideal candidate has a proven track record of delivering impactful data science solutions and shaping enterprise-level data strategies.

Key Responsibilities

Advanced Data Analysis

  • Analyze complex, large-scale datasets to extract actionable insights.
  • Apply advanced statistical methods and machine learning techniques.
  • Formulate and validate hypotheses to support business decisions.

Predictive Modeling & Machine Learning

  • Develop and deploy sophisticated ML models including:
    • Deep learning
    • Ensemble methods
    • Neural networks
  • Lead algorithm development and model optimization.
  • Oversee model deployment into production environments.

Feature Engineering & Data Preparation

  • Lead feature engineering efforts to enhance predictive performance.
  • Work closely with data engineering teams to integrate data from:
    • Data lakes
    • Data warehouses
    • Distributed systems

Visualization & Communication

  • Build compelling visualizations using:
    • Tableau
    • Power BI
    • Python libraries (Matplotlib, Seaborn, etc.)
  • Present complex analytical findings to technical and executive audiences.

Experimentation & Testing

  • Design and analyze A/B tests.
  • Measure and quantify business impact of changes and optimizations.

Data Governance & Ethics

  • Ensure compliance with privacy laws and data protection standards.
  • Promote ethical AI and responsible data practices.

Leadership & Strategy

  • Mentor junior data scientists.
  • Influence organizational data strategy and roadmap.
  • Drive a data-driven culture across business units.
  • Evaluate emerging tools and technologies for innovation opportunities.

Required Qualifications

  • 10–15 years of experience in data science.
  • Master’s or Ph.D. in:
    • Computer Science
    • Statistics
    • Mathematics
    • Engineering
    • Related quantitative field
  • Expert proficiency in:
    • Python, R, or Julia
    • SQL
  • Strong experience with:
    • Machine learning algorithms
    • Big data technologies (Hadoop, Spark)
    • Distributed computing frameworks
  • Experience with data visualization tools (Tableau, Power BI).
  • Strong leadership and communication skills.
  • Demonstrated ability to drive enterprise-level analytics initiatives.

Technical Expertise

  • Machine Learning & AI
  • Statistical Modeling
  • Feature Engineering
  • A/B Testing
  • Big Data Technologies
  • SQL & Data Manipulation
  • Model Deployment (MLOps familiarity preferred)
  • Data Governance & Compliance

Core Competencies

  • Strategic thinking
  • Innovation mindset
  • Cross-functional collaboration
  • Executive-level communication
  • Mentorship and leadership
  • Advanced problem-solving abilities