AI/ML Engineer

VDart Inc; Atlanta (GA); Hybrid; USD 96,000 - 152,000; Part time

Job summary

VDart Inc. is seeking an experienced AI/ML Engineer for hybrid work in Atlanta/Chicago. The contract role focuses on designing, deploying, and operationalizing scalable AI/ML solutions across enterprise apps.

You will collaborate with data scientists, engineers, and business stakeholders to deliver production-ready ML systems, manage model lifecycle, and address data quality in multi-source datasets.

Qualifications

• 5+ years of Python development, data processing, or ML engineering.
• 3+ years building ML solutions with Scikit-learn, TensorFlow or PyTorch.
• 2+ years deploying AI/ML on cloud platforms (AWS, Azure, GCP).
• Experience with data pipelines, feature engineering, and model development.
• Familiarity with MLOps, CI/CD, and API-based integration.

Responsibilities

• Design, develop, train, and deploy enterprise ML models.
• Build data preprocessing, feature engineering, and training pipelines.
• Integrate AI capabilities into enterprise apps via APIs/microservices.
• Evaluate algorithms, optimize for accuracy and performance.
• Implement ML pipelines for training, testing, deployment, monitoring.

Skills

Python

Data processing

Machine learning

ML frameworks

MLOps

SQL

Cloud services

API & microservices

Agile

Tools

Docker

Kubernetes

CI/CD pipelines

LangChain

LlamaIndex

Azure OpenAI

Job description

Role: AI/ML Engineer

Location: Atlanta/Chicago (Hybrid)

Type: Contract

Role Summary:

• We are seeking an experienced Business Consultant AI/ML Engineer to design, develop, and deploy scalable Artificial Intelligence and Machine Learning solutions. The ideal candidate should have strong hands-on experience with Python, machine learning frameworks, data processing, and cloud-based AI/ML services.
• The role will collaborate with data scientists, data engineers, application developers, and business stakeholders to build production-ready ML solutions and integrate AI capabilities into enterprise applications.

Day to Day Job Duties:

• Design, develop, train, and deploy Machine Learning models for enterprise use cases.
• Develop data preprocessing, feature engineering, model training, and evaluation pipelines.
• Build and integrate AI/ML services with enterprise applications using APIs and Microservices.
• Evaluate ML algorithms and optimize models for accuracy, performance, and scalability.
• Develop automated ML pipelines for model training, testing, deployment, and monitoring.
• Collaborate with Data Scientists, Data Engineers, and business teams to translate requirements into AI/ML solutions.
• Implement MLOps practices for model versioning, deployment, monitoring, and lifecycle management.
• Work with structured and unstructured datasets from multiple sources.
• Monitor production models and address model performance, drift, and data-quality issues.
• Participate in code reviews, technical design discussions, and Agile delivery activities.

Basic Qualifications:

• 5+ years of experience in Python development, Data Science, or Machine Learning engineering.
• 3+ years of experience developing ML solutions using Scikit-learn, TensorFlow, PyTorch, or similar frameworks.
• 3+ years of experience with data processing, feature engineering, SQL, and model development.
• 2+ years of experience deploying AI/ML solutions on AWS, Azure, or Google Cloud Platform.
• Nice to Have
• Experience with Generative AI, Large Language Models (LLMs), and Agentic AI.
• Knowledge of RAG, embeddings, vector databases, and semantic search.
• Experience with LLM frameworks such as LangChain, LlamaIndex, or similar technologies.
• Experience with Azure OpenAI, Amazon Bedrock, Vertex AI, or similar AI platforms.
• Knowledge of MLOps tools and model lifecycle management.
• Experience with Docker, Kubernetes, and CI/CD pipelines.
• Familiarity with Spark, Databricks, Snowflake, or other enterprise data platforms.
• Understanding of responsible AI, model governance, security, and data privacy.
• Experience developing AI solutions within Banking, Financial Services, Healthcare, Retail, or other enterprise domains.
• Strong analytical, problem-solving