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Ml Inference Jobs in Alabama (NOW HIRING)

Genuine Parts Company

ML Search Engineer

Birmingham, AL · On-site

Build and integrate ML inference pipelines: embedding models, transformer-based classifiers, LLM-powered query understanding, and reranking services. * Develop event-driven, real-time architectures ...

Frontier Technology Inc.

AI/ML Engineer

Huntsville, AL · Remote

Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference ... Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or ...

Frontier Technology Inc.

AI/ML Engineer

Huntsville, AL · Remote

Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference ... Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or ...

Genuine Parts Company

Search Engineer

Birmingham, AL · On-site

Build and integrate ML inference pipelines: embedding models, transformer-based classifiers, LLM-powered query understanding, and reranking services. * Develop event-driven, real-time architectures ...

Tocaro Blue

Senior Machine Learning Engineer

Birmingham, AL · On-site

$130K - $162K/yr

... C++ inference layers · Advance fusion-aware ML models that integrate Radar with EO/IR, AIS, and cartography for robust classification in GPS-denied or cluttered environments · Collaborate with ...

Tocaro Blue

Staff Machine Learning Engineer

Birmingham, AL · On-site

$155K - $190K/yr

... including C++ inference layers • Advance fusion-aware ML models that integrate Radar with EO/IR, AIS, and cartography for robust classification in GPS-denied or cluttered environments • ...

Tocaro Blue

Staff Machine Learning Engineer

Birmingham, AL · On-site

$155K - $190K/yr

... C++ inference layers · Advance fusion-aware ML models that integrate Radar with EO/IR, AIS, and cartography for robust classification in GPS-denied or cluttered environments · Collaborate with ...

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Ml Inference information

What is ML inference?

ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.

What is the difference between Ml Inference vs Data Scientist?

AspectML InferenceData Scientist
Required CredentialsKnowledge of machine learning models, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentDeploying models in production, real-time data processingData analysis, model development, research
Industry UsageAI product deployment, software companiesResearch institutions, tech firms, consulting

ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.

What are some common challenges faced by ML inference engineers when deploying models to production?

ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.

What are the key skills and qualifications needed to thrive in ML inference?

To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.

Is ML inference a high paying job?

ML inference roles are generally well-paying, especially for those with skills in machine learning frameworks, programming, and cloud platforms. Salaries vary based on experience, location, and industry, but they tend to be higher than average for tech-related positions.
What are popular job titles related to Ml Inference jobs in Alabama? For Ml Inference jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Ml Inference jobs in Alabama look for? The top searched job categories for Ml Inference jobs in Alabama are:
Ml Inference jobs near you

ML Search Engineer

Genuine Parts Company

Birmingham, AL • On-site

Full-time

Medical, Retirement, PTO

Re-posted 21 days ago

Genuine Parts Company rating

7.0

Company rating: 7.0 out of 10

Based on 58 frontline employees who took The Breakroom Quiz

235th of 410 rated retail wholesalers

Job description

Search Engineer (Software Engineer III)
You must be eligible to work in the US without Visa Sponsorship.
ABOUT THE ROLE
We're building intelligent product search that understands intent, learns from behavior, and gets smarter over time. As a Senior Full Stack Engineer on the ML/AI Search team, you'll design and build both the frontend and backend systems that power product discovery for millions of industrial buyers-from scalable retrieval pipelines, APIs, and Frontend interfaces that make AI accessible.
This isn't a research role. You'll own the full lifecycle: prototyping ideas, shipping production-grade services on GCP, and iterating based on real user data. Strong Python and React engineering is the foundation-if you also bring experience in search systems, vector databases, or Elasticsearch, you'll hit the ground running from day one.
WHAT YOU'LL DO
Build & Ship Search and AI-Powered Systems
  • Design, develop, and deploy production Python services end-to-end-from retrieval and ranking pipelines through client-facing APIs.

  • Build and integrate ML inference pipelines: embedding models, transformer-based classifiers, LLM-powered query understanding, and reranking services.

  • Develop event-driven, real-time architectures using GCP services-Cloud Run, Pub/Sub, GKE, Cloud Functions.

  • Write clean, well-tested, observable Python backends; own your services through deployment, monitoring, and on-call

  • Drive frontend architecture decisions, establishing development standards, and creating reusable component libraries.

Contribute to Search Infrastructure
  • Work alongside the Search Architect and ML Architect to implement hybrid retrieval systems combining keyword search, dense vector similarity, and reranking.

  • Build and maintain Elasticsearch indexing pipelines, query services, and relevance tuning tooling.

  • Integrate vector databases (Pinecone, Weaviate, FAISS or similar) into retrieval workflows-even if this is new territory, you'll learn fast.

  • Instrument search pipelines with meaningful metrics: CTR, zero-result rate, latency-feeding the team's A/B experimentation loop.

  • Build clean, responsive, and production-ready interfaces from wireframes or Figma designs.

Own the Engineering Bar
  • Champion CI/CD, observability, testing, and infrastructure-as-code as non-negotiables, not afterthoughts.

  • Lead design sessions with Engineers and Architects; translate product requirements into clean, maintainable technical solutions.

  • Participate in code reviews and knowledge-sharing-actively raising the team's collective skill level.

WHAT YOU BRING
Must-Haves
  • Strong Python and React foundation: 6+ years of professional backend or full-stack engineering experience with a deep Python/React (e.g., Next.js, Vite.js, Remix.js, Gatsby.js) focus-async patterns, type annotations, testing, and production-grade service/component design.

  • Cloud-native experience: Proven experience designing and deploying cloud-native applications (

GCP strongly preferred; AWS or Azure considered).
  • Hands-on experience building resilient high throughput microservices and RESTful/gRPC APIs.

  • Solid understanding of containerization (Docker), orchestration (Kubernetes), and serverless paradigms.

  • Strong grounding in SOLID design principles and software craftsmanship.

  • Good communicator who thrives in cross-functional, agile teams alongside ML engineers, architects, and product owners.

  • Comfort using AI tools to accelerate development throughput.

  • Strong experience of using and managing Monorepos

  • Strong understanding of relational (e.g., PostgreSQL, MySQL, Oracle) and non-relational databases (e.g., MongoDB, DynamoDB).

  • Mentorship: Provide guidance and technical knowledge sharing to mid-level and junior developers.

Strongly Preferred - Search & ML
You don't need all of these on day one-but the more you bring, the faster you'll contribute:
  • Search systems: Experience with search platforms:

Elasticsearch, OpenSearch, Solr, or Algolia-index management, query DSL, relevance tuning.
  • Vector search: Familiarity with vector search concepts and tooling:

embeddings, approximate nearest neighbor (ANN), FAISS, Pinecone, Weaviate, or similar.
  • Exposure to ML/AI patterns: RAG pipelines, LLM integration, prompt engineering, or fine-tuning workflows.

  • Experience with AI orchestration frameworks such as LangChain, LangGraph, or Google ADK.

  • Infrastructure-as-code experience (Terraform, Pulumi, OpenTofu) and mature CI/CD pipeline ownership.

WHO YOU ARE
Fearless Builder
A working proof-of-concept beats a thousand slide decks. Speed and quality are both non-negotiable.
Relentless Learner
You pick up new technologies fast and have a genuine eagerness to master whatever comes next.
Architecture-Minded
You design scalable, fault-tolerant services as second nature and aren't afraid to challenge the status quo.
Ownership-Driven
Code isn't done until it's tested, documented, and monitored. Your name on a release means something.
Search-Curious
You may not have built a search system yet-but you're excited by the challenge and ready to go deep.
Team Multiplier
You give and welcome candid feedback and actively make the people around you better.
PHYSICAL DEMANDS:
LICENSES & CERTIFICATIONS: None required.
SUPERVISORY RESPONSIBILITY: No Supervisory Responsibility
BUDGET RESPONSIBILITY: No
COMPANY INFORMATION: Motion Industries offers an excellent benefits package which includes options for healthcare coverage, 401(k), tuition reimbursement, vacation, sick, and holiday pay.
DISCLAIMER: This job description illustrates the general nature and level of work performed by employees within this job classification. It is not intended to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and skills required. Management retains the right to add or modify duties at any time.
Not the right fit? Let us know you're interested in a future opportunity by joining our Talent Community on jobs.genpt.com or create an account to set up email alerts as new job postings become available that meet your interest!
GPC conducts its business without regard to sex, race, creed, color, religion, marital status, national origin, citizenship status, age, pregnancy, sexual orientation, gender identity or expression, genetic information, disability, military status, status as a veteran, or any other protected characteristic. GPC's policy is to recruit, hire, train, promote, assign, transfer and terminate employees based on their own ability, achievement, experience and conduct and other legitimate business reasons.

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