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Ml Inference Jobs in Gretna, LA (NOW HIRING)

Deloitte

AI Engineer Consultant

New Orleans, LA · Hybrid

Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills). A successful candidate would possess ...

Deloitte

Google AI Lead Architect

New Orleans, LA

$53 - $72.75/hr

Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an ...

Deloitte

Google AI Architect

New Orleans, LA · On-site

Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an ...

Ochsner Health

Senior AI Scientists

New Orleans, LA

Serve as a subject matter expert in ML, advanced AI, GenAI/LLMs, Snowflake Cortex, Epic deployment, applied statistics, causal inference, and experiment design. Provide technical mentorship through ...

Ochsner Health

Senior AI Scientists

New Orleans, LA · On-site

Serve as a subject matter expert in ML, advanced AI, GenAI/LLMs, Snowflake Cortex, Epic deployment, applied statistics, causal inference, and experiment design. Provide technical mentorship through ...

All JobsMl Inference JobsMl Inference Jobs in Gretna, LA

Ml Inference information

See Gretna, LA salary details

$32.4K

$105.9K

$169.5K

How much do ml inference jobs pay per year?

As of Aug 24, 2026, the average yearly pay for ml inference in Gretna, LA is $105,904.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,000.00 and $117,300.00 per year, depending on experience, location, and employer.

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 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.

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 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.

Ml Inference jobs near you

AI Engineer Consultant

New Orleans, LA • Hybrid

Deloitte
Finance and Insurance • 10K+ employees

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

46th of 151 rated financial services

Good employer

Recommended by students

Paid breaks

Learn more about Deloitteexternal

Full-time

Re-posted 29 days ago

Job description

Position Summary

Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that power Human Capital AI products and analytics. You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non-functional requirements), partnering closely with product, data science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI solutions.

This role is hands-on and delivery-oriented: you will ship production pipelines and services that support model training, real-time inference, and LLM applications using Claude-, GPT/Codex-, and Gemini-class models, and more implemented with strong governance, observability, and cost/performance discipline.

Recruiting for this role ends on 08/30/2026.

Work you'll do

As an AI Engineer Consultant on the HC Forward team, you will design, build, and run the trusted, governed data + feature + retrieval layer used by AI/ML and GenAI solutions. You will deliver reproducible datasets and features, operationalize quality and lineage, and enable secure consumption patterns for both predictive ML and LLM-based experiences.

  • Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product needs into secure, scalable technical designs and delivered solutions (APIs, services, pipelines, containers/serverless) meeting availability, performance, and security expectations.
  • Build and operationalize LLM-enabled capabilities (e.g., copilots, HR knowledge assistants, summarization, policy Q&A) using Claude/GPT(Codex)/Gemini, including secure endpoints, tool/function calling, and reusable prompt/context patterns.
  • Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector/hybrid search, and retrieval/evaluation telemetry.
  • Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills).

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

Qualifications

Required:

  • Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
  • 2+ years building and delivering LLM/GenAI solutions with Claude/GPT(Codex)/Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration.
  • 2+ years implementing RAG/retrieval (document processing, embeddings, vector/hybrid search) with enterprise governance controls.
  • 2+ years of modern data & AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals.
  • 2+ years building production, real-time inference services (API design, latency/performance, reliability patterns).
  • 2+ years leading platform/integration engineering across enterprise systems; strong API/integration experience (REST, GraphQL, event-driven, microservices, middleware).
  • 2+ years DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes, observability/monitoring).
  • 2+ years leading security/compliance efforts; familiarity with enterprise security controls (IAM, encryption, secrets, audit logging) and data/privacy (PII, retention, access controls); SOC 2/GDPR/HIPAA exposure a plus.
  • Ability to travel 0-25%, on average, based on client and project needs.
  • Must be legally authorized to work in the United states without the need for employer sponsorship, now or at any time in the future

Preferred:

  • Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML).
  • 2+ years of experience with Human Capital platforms and integrations (e.g., Workday, SAP SuccessFactors, Oracle HCM, Salesforce) and HR data domains.
  • 2+ years of experience operationalizing LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version management).
  • 2+ years of cloud experience on AWS/Azure/GCP (one or more), including managed data platforms and scalable compute patterns.
  • 2+ years of experience with structured problem solving, translating business needs into requirements, acceptance criteria, and shippable increments.
  • 2+ years of experience with stakeholder communication: ability to explain AI/GenAI trade-offs (quality vs. latency vs. cost vs. risk) and document decisions.
  • 2+ years of experience collaborating across product, data science/ML, data engineering, platform, and security.
  • 2+ years of experience with treat testing, monitoring, and operational readiness as core responsibilities.
  • 2+ years of experience with ethics and privacy awareness being able to recognize consent/PII/bias boundaries and escalate appropriately.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $91,100 to $179,500.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Deloitte is committed to providing reasonable accommodations for people with disabilities. If you require a reasonable accommodation to participate in the recruiting process, please direct your inquiries to the Global Call Center (GCC) at USTalentCICInbox@deloitte.com.

For more information about Human Capital, visit our landing page at:https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-human-capital-consulting-jobs.html

#HCFY27  #HRSTFY27

Qualifications:

Position Summary

Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that power Human Capital AI products and analytics. You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non-functional requirements), partnering closely with product, data science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI solutions.

This role is hands-on and delivery-oriented: you will ship production pipelines and services that support model training, real-time inference, and LLM applications using Claude-, GPT/Codex-, and Gemini-class models, and more implemented with strong governance, observability, and cost/performance discipline.

Recruiting for this role ends on 08/30/2026.

Work you'll do

As an AI Engineer Consultant on the HC Forward team, you will design, build, and run the trusted, governed data + feature + retrieval layer used by AI/ML and GenAI solutions. You will deliver reproducible datasets and features, operationalize quality and lineage, and enable secure consumption patterns for both predictive ML and LLM-based experiences.

  • Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product needs into secure, scalable technical designs and delivered solutions (APIs, services, pipelines, containers/serverless) meeting availability, performance, and security expectations.
  • Build and operationalize LLM-enabled capabilities (e.g., copilots, HR knowledge assistants, summarization, policy Q&A) using Claude/GPT(Codex)/Gemini, including secure endpoints, tool/function calling, and reusable prompt/context patterns.
  • Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector/hybrid search, and retrieval/evaluation telemetry.
  • Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills).

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

Qualifications

Required:

  • Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
  • 2+ years building and delivering LLM/GenAI solutions with Claude/GPT(Codex)/Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration.
  • 2+ years implementing RAG/retrieval (document processing, embeddings, vector/hybrid search) with enterprise governance controls.
  • 2+ years of modern data & AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals.
  • 2+ years building production, real-time inference services (API design, latency/performance, reliability patterns).
  • 2+ years leading platform/integration engineering across enterprise systems; strong API/integration experience (REST, GraphQL, event-driven, microservices, middleware).
  • 2+ years DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes, observability/monitoring).
  • 2+ years leading security/compliance efforts; familiarity with enterprise security controls (IAM, encryption, secrets, audit logging) and data/privacy (PII, retention, access controls); SOC 2/GDPR/HIPAA exposure a plus.
  • Ability to travel 0-25%, on average, based on client and project needs.
  • Must be legally authorized to work in the United states without the need for employer sponsorship, now or at any time in the future

Preferred:

  • Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML).
  • 2+ years of experience with Human Capital platforms and integrations (e.g., Workday, SAP SuccessFactors, Oracle HCM, Salesforce) and HR data domains.
  • 2+ years of experience operationalizing LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version management).
  • 2+ years of cloud experience on AWS/Azure/GCP (one or more), including managed data platforms and scalable compute patterns.
  • 2+ years of experience with structured problem solving, translating business needs into requirements, acceptance criteria, and shippable increments.
  • 2+ years of experience with stakeholder communication: ability to explain AI/GenAI trade-offs (quality vs. latency vs. cost vs. risk) and document decisions.
  • 2+ years of experience collaborating across product, data science/ML, data engineering, platform, and security.
  • 2+ years of experience with treat testing, monitoring, and operational readiness as core responsibilities.
  • 2+ years of experience with ethics and privacy awareness being able to recognize consent/PII/bias boundaries and escalate appropriately.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $91,100 to $179,500.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Deloitte is committed to providing reasonable accommodations for people with disabilities. If you require a reasonable accommodation to participate in the recruiting process, please direct your inquiries to the Global Call Center (GCC) at USTalentCICInbox@deloitte.com.

For more information about Human Capital, visit our landing page at:https://www2....

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