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Machine Learning Engineer Jobs in Birmingham, AL

Varsity Tutors

Machine Learning Tutor

Birmingham, AL · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Pwc

CTIO AI Engineering Manager

Birmingham, AL

$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 ...

Pwc

NGA AI Engineer 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 ...

4pconsultinginc

Data Scientist III (IT)

Birmingham, AL · On-site

This role requires strong expertise in statistics, machine learning, and programming , with the ability to transform raw data into actionable insights. The ideal candidate has hands-on experience ...

Pwc

NGA AI Engineer Senior Manager

Birmingham, AL · On-site

$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 ...

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Machine Learning Engineer information

See Birmingham, AL salary details

$29.5K

$120.7K

$181.4K

How much do machine learning engineer jobs pay per year?

As of Jun 10, 2026, the average yearly pay for machine learning engineer in Birmingham, AL is $120,725.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,200.00 and $145,300.00 per year, depending on experience, location, and employer.

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.

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 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.

What jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.
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 98% Full Time, and 2% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $120,725 per year, or $58 per hour.

Machine Learning Engineer / Predictive Analyst

Vaco by Highspring

Birmingham, AL • On-site

Other

Dental, Vision, Retirement

Posted 22 days ago

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 team’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 individual’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 company’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.

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