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Mlops Jobs in Decatur, GA (NOW HIRING)

AI/ML Evaluation Engineer

Atlanta, GA · On-site

$79K - $105K/yr

Your work will also contribute to enterprise MLOps capabilities, data governance standards, and ethical AI practices within regulated public health environments. This position is located in Atlanta ...

Senior ML Engineer II

Atlanta, GA · On-site

$100K - $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 II

Atlanta, GA · On-site

$100K - $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 II

Atlanta, GA · On-site

$100K - $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 II

Atlanta, GA

$100K - $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 II

Atlanta, GA · On-site

$100K - $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 ...

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

$100K - $131K/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 ...

Senior Agentic (AI) Engineer

Atlanta, GA · Remote

$107K - $146K/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 · On-site +1

$100K - $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 ...

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

Senior ML Engineer

Atlanta, GA · On-site

$100K - $138K/yr

... MLOps practices for continuous integration, continuous delivery (CI/CD), model versioning, and performance monitoring (latency, throughput, accuracy). • Establish effective feedback loops from end ...

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Mlops information

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 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 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:
What job categories do people searching Mlops jobs in Decatur, GA look for? The top searched job categories for Mlops jobs in Decatur, GA are:
What cities near Decatur, GA are hiring for Mlops jobs? Cities near Decatur, GA with the most Mlops job openings:
Infographic showing various Mlops job openings in Decatur, GA as of July 2026, with employment types broken down into 89% Full Time, 6% Part Time, 1% Temporary, and 4% Contract. Highlights an 72% Physical, 4% Hybrid, and 24% Remote job distribution.
AI/ML Evaluation Engineer

AI/ML Evaluation Engineer

Booz Allen Hamilton

Atlanta, GA • On-site

$79K - $105K/yr

Other

Medical, Life, Retirement, PTO

Posted 13 days ago


Booz Allen Hamilton rating

8.8

Company rating: 8.8 out of 10

Based on 47 frontline employees who took The Breakroom Quiz

9th of 58 rated business consultants


Job description

Job Number: R0243409
AI/ML Evaluation Engineer
The Opportunity:
As an experience d engineer, you know that machine learning ( ML ) and AI evaluation are critical to understanding and operationalizing massive datasets in support of public health and safety missions. Your ability to evaluate, optimize, and deploy AI-driven systems makes you an integral part of delivering mission-focused solutions for scientists, analysts, and leadership teams.
In this role, you'll help define and implement scientific AI evaluation and enablement initiatives by translating advanced AI capabilities into practical, mission-specific workflows. You'll collaborate with a large community of ML engineers, data scientists, architects, and product teams to design scalable ML and Generative AI solutions, including AI agents, retrieval-augmented generation ( RAG ) pipelines, and enterprise AI evaluation frameworks.
You'll apply technical expertise across AI evaluation, retrieval optimization, memory and state management, and AI agent architecture to support real-time insights and decision-making. Your work will also contribute to enterprise MLOps capabilities, data governance standards, and ethical AI practices within regulated public health environments. This position is located in Atlanta, GA.
What You'll Work On:
  • Build and maintain scalable data pipelines using PySpark and Palantir Foundry to support AI, analytics, and scientific evaluation workflows.
  • Design and implement ML and Generative AI workflows, including AI agents, RAG pipelines, and AI evaluation frameworks.
  • Integrate advanced AI technologies such as Codex and Claude, to support mission-specific workflows, real-time insights, and decision-making capabilities.
  • Develop evaluation strategies covering model quality, retrieval optimization, benchmarking, and performance monitoring for deployed AI systems.
  • Design AI architectures supporting memory, state management, structured and unstructured public health data interaction, and scalable agent orchestration.
  • Establish data governance, privacy, anonymization, documentation, and ethical AI standards across AI / ML systems and public health data environments.

Join us. The world can't wait.
You Have:
  • 5+ years of experience with Generative AI, LLMs, AI agents, or RAG applications, and designing, developing, and deploying ML models and AI solutions using Python
  • 3+ years of experience with AI agents and AI evaluation strategies in enterprise environments
  • 2+ years of experience with Deep Research evaluation met hodologies and AI evaluation workflows
  • Experience with ML frameworks such as TensorFlow or PyTorch, for production-grade model development
  • Experience with data engineering using PySpark, SQL, and Palantir Foundry, including Foundry AIP
  • Experience with MLOps platforms such as MLflow and cloud environments, including Azure
  • Knowledge of public health, healthcare, or government data systems and asso cia ted governance practices
  • Ability to design and optimize AI systems involving retrieval workflows, memory or state management, and real-time decision-support capabilities
  • Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
  • Bachelor's degree in CS, Engineering, or Data Science

Nice If You Have:
  • Experience working in healthcare, biomedical, or government public health AI / ML environments
  • Experience with conversational AI, chatbot systems, or full-stack AI application development
  • Experience with containerization, CI / CD, orchestration, and production MLOps pipelines
  • Experience with Agile delivery environments and tools such as Jira
  • Experience writing technical documentation and presenting AI / ML solutions to various audiences
  • Experience integrating enterprise AI tools such as Codex, Claude, or similar AI enablement platforms
  • Knowledge of enterprise AI governance, compliance, and ethical AI frameworks
  • Knowledge of AI systems for retrieval, ranking, and scientific evaluation use cases
  • Ability to collaborate effectively in matrixed, cross-functional organizations
  • Master's degree in CS, Data Science, ML, or a related field

Vetting:
Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client .
Compensation
At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen's benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.
Salary at Booz Allen is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $128,700.00 to $292,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen's total compensation package for employees. This posting will close within 90 days from the Posting Date.
Identity Statement
As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
Candidate AI Usage Policy
AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.
Work Model
Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.
  • Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.
  • Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.
  • Onsite: If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role.

Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.

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About Booz Allen Hamilton

Sourced by ZipRecruiter

Booz Allen Hamilton is a leading provider of management and technology consulting services to the US government in defense, intelligence, and civil markets. Headquartered in McLean, Virginia, the firm also serves major corporations, institutions, and not-for-profit organizations. Founded in 1914 by Edwin G. Booz, the company has a long-standing tradition of helping clients achieve success by delivering a wide range of consulting services that include strategic planning, human capital and learning, communication, systems development, and others. The company's mission is to empower people to change the world, and it has a reputation for maintaining the highest standards of integrity and-excellence.

Industry

It services

Company size

10,000+ Employees

Headquarters location

McLean, VA, US

Year founded

1914