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Mlops Jobs in Decatur, GA (NOW HIRING)

Senior ML Engineer I

Atlanta, GA

$100.50K - $138K/yr

MLOps & Deployment: * Deploy, manage, and monitor LMs and agentic components on Google Cloud Platform (GCP) using services like Vertex AI, GKE, Cloud Functions, and Cloud Run. * Implement robust ...

Senior ML Engineer I

Atlanta, GA

$100.50K - $138K/yr

MLOps & Deployment: * Deploy, manage, and monitor LMs and agentic components on Google Cloud Platform (GCP) using services like Vertex AI, GKE, Cloud Functions, and Cloud Run. * Implement robust ...

Senior ML Engineer I

Atlanta, GA · On-site

$100.50K - $138K/yr

MLOps & Deployment: * Deploy, manage, and monitor LMs and agentic components on Google Cloud Platform (GCP) using services like Vertex AI, GKE, Cloud Functions, and Cloud Run. * Implement robust ...

Machine Learning Engineer II

Atlanta, GA · On-site

$93.80K - $128.40K/yr

You bring a strong engineering background (cloud, infrastructure, CI/CD, MLOps) and are excited to create "paved paths" for software engineers to use AI tools, models, and patterns safely and ...

Cloud Developer

Alpharetta, GA · On-site

$55 - $75.25/hr

... with MLOps principles for managing the machine learning lifecycle • Experience with data management and engineering principles in a cloud context Additional Qualifications a Plus: • Experience ...

Lead Engineer- Cloud Product

Alpharetta, GA · On-site

$100.10K - $131.80K/yr

Experienced with modern ML frameworks (TensorFlow, PyTorch, Hugging Face, etc.) and MLOps tools (Kubeflow, MLflow, Vertex AI Pipelines). * Proven record developing and deploying secure, enterprise ...

AI/ML Engineer

Atlanta, GA · Remote

$140K - $220K/yr

Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration). * Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and ...

AI/ML Engineer

Atlanta, GA · Remote

$140K - $220K/yr

Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration). * Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and ...

AI/ML Engineer

Atlanta, GA · On-site +1

$140K - $220K/yr

Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration). * Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and ...

AI/ML Engineer

Atlanta, GA · Remote

$140K - $220K/yr

Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration). * Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and ...

Senior Agentic (AI) Engineer

Atlanta, GA · On-site +1

$100.50K - $138K/yr

Drive production MLOps: deployment, versioning, traffic shaping, cost/latency budgets, tracing, and on-call playbooks for agent incidents. * Partner with security and compliance to keep agents inside ...

Senior Agentic (AI) Engineer

Atlanta, GA · Remote

$107K - $146.90K/yr

Drive production MLOps: deployment, versioning, traffic shaping, cost/latency budgets, tracing, and on-call playbooks for agent incidents. * Partner with security and compliance to keep agents inside ...

Implement MLOps standard methodologies, including model versioning and lifecycle management, drift detection and performance monitoring, retraining schedules and automated pipelines, and ...

Sr. Director Data & AI Platforms

Atlanta, GA

$64.75 - $86.50/hr

MLOps & AI Lifecycle Platforms: Deep experience with MLOps platforms (MLflow, Kubeflow, or cloud-native equivalents), including automated retraining pipelines, model governance, drift detection, A/B ...

Contribute to CI/CD pipelines, observability instrumentation (OpenTelemetry, structlog), and MLOps best practices for model lifecycle management. Collaboration and Strategy * Partner with Product ...

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Showing results 1-20

Mlops information

What are the key skills and qualifications needed to thrive as an MLOps Engineer, and why are they important?

To thrive as an MLOps Engineer, you need a strong background in machine learning, software engineering, and DevOps principles, often supported by a degree in computer science or a related field. Proficiency with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (e.g., AWS, Azure, GCP), and ML frameworks is typically required, along with certifications in cloud or DevOps technologies. Strong problem-solving skills, collaboration, and communication abilities help MLOps professionals excel in cross-functional teams and manage complex workflows. These skills are vital for reliably deploying, monitoring, and scaling machine learning models in production environments, ensuring efficiency and robustness.

What are some common challenges faced by MLOps professionals when deploying machine learning models to production?

MLOps professionals often encounter challenges such as ensuring reproducibility of models, managing version control for both code and data, and maintaining model performance over time. Handling continuous integration and deployment (CI/CD) pipelines for ML models can be complex, especially when dealing with large datasets and evolving algorithms. Additionally, coordinating with data scientists, software engineers, and DevOps teams to streamline workflows and monitor models post-deployment are key responsibilities that require both technical expertise and strong collaboration skills.

What are MLOps?

MLOps, short for Machine Learning Operations, is a set of practices that combines machine learning, DevOps, and data engineering to automate and streamline the deployment, monitoring, and maintenance of machine learning models in production. MLOps aims to improve collaboration between data scientists and operations teams, ensuring that models are robust, scalable, and easily updated. It covers the entire machine learning lifecycle, from data preparation to model training, deployment, and ongoing monitoring. By implementing MLOps, organizations can accelerate the development and deployment of reliable machine learning solutions.

What is the difference between Mlops vs Data Engineer?

AspectMlopsData Engineer
Primary FocusDeploying, managing, and monitoring machine learning models in productionBuilding and maintaining data pipelines and infrastructure for data processing
Skills & CertificationsMachine learning, DevOps, cloud platforms, scriptingSQL, ETL, data warehousing, programming
Work EnvironmentCollaborates with data scientists, software engineers, and DevOps teamsWorks with data analysts, data scientists, and software developers
Industry UsageAI/ML projects, production environments, cloud servicesData infrastructure, analytics, big data processing

While both Mlops and Data Engineers work closely with data and cloud technologies, Mlops specialists focus on deploying and maintaining machine learning models in production, ensuring their scalability and reliability. Data Engineers primarily build data pipelines and infrastructure to support data analysis and ML workflows. Understanding these distinctions helps organizations assign the right roles for their AI and data projects.

What are the most commonly searched types of Mlops jobs in Decatur, GA? The most popular types of Mlops jobs in Decatur, GA are:
What are popular job titles related to Mlops jobs in Decatur, GA? For Mlops jobs in Decatur, GA, the most frequently searched job titles are:
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$100.50K - $138K/yr

Full-time

Medical, Retirement, PTO

Posted 9 days ago


Job description

ABOUT THIS POSITION

We are seeking a highly skilled and innovative Senior ML Engineer with a passion for building robust, efficient, and domain-specific AI systems using Language Models (LMs) and agentic architectures. As a core member of the team, you will be instrumental in developing the entire ML pipeline, from sophisticated data extraction techniques to fine-tuning specialized LMs and orchestrating their interactions within a multi-agent framework.
This is a unique opportunity to apply state-of-the-art Generative AI and NLP techniques to a real-world, high-impact problem, leveraging the latest research in agentic AI and LMs to deliver economical and powerful solutions.

WHAT YOU'LL DO

Data Pipeline & Knowledge Base Construction:

  • Design, implement, and optimize robust pipelines for ingesting, parsing, and extracting structured information from complex documents (leveraging OCR, document layout analysis, Named Entity Recognition (NER), and Relationship Extraction (RE).

  • Develop rich, nested JSON schemas for representing structured data and ensure scalable storage

  • Generate and manage high-quality vector embeddings for efficient retrieval-augmented generation (RAG) within a Vector Database.

Language Model (LM) Development & Fine-tuning:

  • Research, select, and experiment with appropriate open-source Language Models (Large & Small) (e.g., Phi-3, Mistral, Llama, Nemotron-H families) for specialized tasks.

  • Design and execute efficient fine-tuning strategies (e.g., LoRA, QLoRA, full fine-tuning) on curated, domain-specific datasets to achieve precise performance for tasks like coverage determination, code lookups, and policy rule application.

  • Explore and implement knowledge distillation techniques to transfer capabilities from larger models to smaller, more efficient LMs.

Agentic System Design & Implementation:

  • Build and maintain the core agentic framework, including the orchestrator that intelligently routes queries and coordinates interactions between various specialized LM tools.

  • Develop and integrate "tools" (specialized LMs and external APIs) that perform atomic medical necessity tasks, ensuring strict behavioral alignment and structured outputs.

MLOps & Deployment:

  • Deploy, manage, and monitor LMs and agentic components on Google Cloud Platform (GCP) using services like Vertex AI, GKE, Cloud Functions, and Cloud Run.

  • Implement robust MLOps practices for continuous integration, continuous delivery (CI/CD), model versioning, and performance monitoring (latency, throughput, accuracy).

Continuous Improvement & Research:

  • Establish effective feedback loops from end-user interactions and system logs to identify areas for model improvement.

  • Curate and expand training datasets, ensuring data privacy (PHI/PII masking) and legal compliance.

  • Stay abreast of the latest research in LMs, agentic AI, NLP, and document understanding, applying relevant advancements to our system.

Collaboration:

  • Work closely with subject matter experts, product managers, and other engineers to translate complex requirements into technical solutions and evaluate system performance.

WHAT YOU'LL NEED

  • Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.

  • 3+ years of professional experience in Machine Learning Engineering, with a strong focus on NLP.

  • Proven experience with Language Models (LMs), including model selection, fine-tuning, and deployment.

  • Strong proficiency in Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers).

  • Solid understanding and hands-on experience with core NLP techniques and architectures, especially Transformers.

  • Experience with cloud platforms, particularly Google Cloud Platform (GCP), including services like Vertex AI, Cloud Storage, and compute services.

  • Familiarity with MLOps principles and tools for model serving, monitoring, and pipeline automation.

  • Excellent problem-solving skills, attention to detail, and ability to work independently and collaboratively.

  • Active use of artificial intelligence (AI) tools and techniques to enhance performance, drive innovation, and improve decision-making across business functions.

  • Ability to leverage AI tools and platforms to streamline workflows, improve decision-making, and drive innovation.

  • Curiosity and adaptability in exploring emerging AI technologies, with a mindset for continuous learning and experimentation.

What Will Make You Stand Out (Preferred Qualifications):

  • Hands-on experience building or contributing to agentic AI systems or multi-agent frameworks.

  • Direct experience with document processing technologies such as OCR, layout parsing, Document AI, or custom information extraction from unstructured text.

  • Experience with Vector Databases (e.g., pgvector, Pinecone, Weaviate, Qdrant) and RAG architectures.

  • Exposure to the healthcare domain, particularly understanding medical terminology, CPT/ICD codes, or regulatory documents.

ABOUT WAYSTAR

Through a smart platform and better experience, Waystar helps providers simplify healthcare payments and yield powerful results throughout the complete revenue cycle.

Waystar's healthcare payments platform combines innovative, cloud-based technology, robust data, and unparalleled client support to streamline workflows and improve financials so providers can focus on what matters most: their patients and communities. Waystar is trusted by 1M+ providers, 1K+ hospitals and health systems, and is connected to over 5K commercial and Medicaid/Medicare payers. We are deeply committed to living out our organizational values: honesty; kindness; passion; curiosity; fanatical focus; best work, always; making it happen; and joyful,optimistic & fun.

Waystar products have won multiple Best in KLAS or Category Leader awards since 2010 and earned multiple #1 rankings from Black Book surveys since 2012. The Waystar platform supports more than 500,000 providers, 1,000 health systems and hospitals, and 5,000 payers and health plans. For more information, visit waystar.comor follow @Waystaron Twitter.

WAYSTAR PERKS

  • Competitive total rewards (base salary + bonus, if applicable)
  • Customizable benefits package (3 medical plans with Health Saving Account company match)
  • We offer generous paid time off for our non-exempt team members, starting with 3 weeks +13 paid holidays, including 2 personal floating holidays. We also offer flexible time off for our exempt team members + 13 paid holidays
  • Paid parental leave (including maternity + paternity leave)
  • Education assistance opportunities and free LinkedIn Learning access
  • Free mental health and family planning programs, including adoption assistance and fertility support
  • 401(K) program with company match
  • Pet insurance
  • Employee resource groups

Waystar is proud to be an equal opportunity workplace. We celebrate, value, and support diversity and inclusion. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.