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Machine Learning Engineer Jobs in Birmingham, AL

Pwc

CTIO 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 ...

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 ...

Deploy

Data, Analytics & AI Engineer

Birmingham, AL · On-site

$107K - $128K/yr

Data, Analytics & AI Engineer Help Build the Future of Data, Analytics & AI Are you passionate ... Drive AI Innovation Design, prototype, and deploy AI and Machine Learning solutions. Build ...

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 ...

Mindlance

Data Scientist 3

Birmingham, AL · On-site

... engineering efforts to identify and select critical data features, enhancing the predictive power of machine learning models. • Formulate, implement, and test hypotheses, providing robust ...

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 ...

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Showing results 21-40

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 Sep 7, 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 is a machine learning engineer?

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 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 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 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 August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $120,681 per year, or $58 per hour.

ML Search Engineer

Seneca Resources Company, LLC

Birmingham, AL • On-site

$130K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 11 days ago

Job description

Position Title: Full Stack Engineer - AI Search & Product Discovery
Location: Remote
Position Status: Full Time
About the Role
We're transforming how millions of industrial buyers discover products through intelligent search experiences powered by AI, machine learning, and modern search technologies.
As a Full Stack Engineer III on our AI Search & Product Discovery team, you'll build the frontend applications, backend services, and search infrastructure that power highly relevant, personalized search experiences at scale. You'll work across the full development lifecycle, from rapid prototyping and experimentation to deploying production-grade solutions and continuously optimizing performance based on real user behavior.
This is an ideal opportunity for an engineer who enjoys solving complex problems at the intersection of full-stack development, search engineering, cloud-native architecture, machine learning, and AI-driven user experiences.
What You'll Do
Build AI-Powered Search Experiences
  • Design, develop, and deploy scalable Python services that power search retrieval, ranking, recommendation, and discovery experiences.
  • Build and integrate machine learning inference pipelines, including embeddings, transformer models, query understanding, reranking services, and LLM-powered features.
  • Develop robust APIs and microservices that support high-volume search workloads and customer-facing applications.
  • Collaborate with product, engineering, and AI teams to translate business goals into impactful search solutions.
  • Continuously improve search relevance, performance, and user engagement through experimentation and data-driven decision making.

Develop Modern Full-Stack Applications
  • Build responsive, accessible, and performant user interfaces using React and modern JavaScript frameworks.
  • Create reusable frontend components and establish engineering standards that improve consistency and developer productivity.
  • Partner with UX and Product teams to transform wireframes and Figma designs into intuitive customer experiences.
  • Contribute to frontend architecture decisions that support long-term scalability and maintainability.

Advance Search & AI Infrastructure
  • Implement hybrid search architectures that combine keyword search, vector search, semantic retrieval, and AI-powered ranking.
  • Build and maintain Elasticsearch/OpenSearch indexing pipelines, query services, and relevance tuning capabilities.
  • Integrate vector databases and retrieval systems such as Pinecone, Weaviate, FAISS, or similar technologies.
  • Develop and optimize Retrieval-Augmented Generation (RAG) and LLM-powered search workflows.
  • Instrument search systems with meaningful metrics, including click-through rate, latency, engagement, and zero-result rates to drive ongoing optimization.

Build Cloud-Native Systems
  • Develop event-driven, distributed systems using Google Cloud Platform (GCP) services such as Cloud Run, GKE, Pub/Sub, and Cloud Functions.
  • Deploy, monitor, and maintain production services using modern DevOps and observability practices.
  • Own service reliability through testing, monitoring, troubleshooting, and operational excellence.

Contribute to Engineering Excellence
  • Participate in architecture discussions, technical design reviews, and code reviews.
  • Mentor peers through collaboration and knowledge sharing.
  • Champion engineering best practices, software craftsmanship, and continuous improvement.

Required Qualifications
  • 4+ years of professional experience in Full Stack Engineering, Backend Engineering, or Software Development.
  • Strong hands-on experience building applications with Python and React.
  • Experience with modern frontend frameworks such as Next.js, Remix, Vite, Gatsby, or similar technologies.
  • Proven experience building and supporting scalable microservices, REST APIs, and/or gRPC services.
  • Experience deploying and operating cloud-native applications in GCP, AWS, or Azure.
  • Experience with Docker, containerized applications, and serverless architectures.
  • Strong understanding of software design patterns, SOLID principles, testing strategies, and maintainable code practices.
  • Experience working with relational and NoSQL databases such as PostgreSQL, MySQL, Oracle, MongoDB, DynamoDB, or similar platforms.
  • Strong communication skills with the ability to collaborate effectively across engineering, product, and architecture teams.
  • Comfortable leveraging AI-assisted development tools to improve productivity and quality.

Preferred Qualifications
Search Engineering
  • Elasticsearch, OpenSearch, Solr, Algolia, or other enterprise search platforms.
  • Search relevance tuning, query optimization, indexing strategies, and ranking algorithms.
  • Large-scale search infrastructure and information retrieval systems.

AI & Machine Learning
  • Generative AI, Large Language Models (LLMs), and AI-powered search experiences.
  • Retrieval-Augmented Generation (RAG).
  • Prompt engineering and LLM orchestration.
  • LangChain, LangGraph, Google ADK, or similar frameworks.
  • Machine learning model deployment and inference pipelines.

Vector Search & Semantic Retrieval
  • Embeddings and semantic search architectures.
  • Approximate Nearest Neighbor (ANN) search.
  • Pinecone, Weaviate, FAISS, Milvus, or similar vector database technologies.

Additional Experience
  • Monorepo development environments.
  • Event-driven architectures.
  • Distributed systems at scale.
  • A/B testing and experimentation frameworks.

About Seneca Resources:
At Seneca Resources, we are more than just a staffing and consulting firm, we are a trusted career partner. With offices across the U.S. and clients ranging from Fortune 500 companies to government organizations, we provide opportunities that help professionals grow their careers while making an impact.
When you work with Seneca, you're choosing a company that invests in your success, celebrates your achievements, and connects you to meaningful work with leading organizations nationwide. We take the time to understand your goals and match you with roles that align with your skills and career path. Our consultants and contractors enjoy competitive pay, comprehensive health, dental, and vision coverage, 401(k) retirement plans, and the support of a dedicated team who will advocate for you every step of the way.

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