AI/ML Engineer

7Th Sky Tech; Charlotte (NC); Hybrid; USD 120,000 - 180,000; Full time

Job summary

7Th Sky Tech in Charlotte, NC is seeking an experienced AI/ML Engineer to design, develop, deploy, and maintain AI solutions. The role involves collaborating with data scientists, software engineers, product teams, and business stakeholders to deliver production-ready ML systems.

The ideal candidate will have strong Python, ML, DL, NLP, Generative AI, LLMs, and MLOps experience, with hands-on cloud deployment and containerization capabilities.

Qualifications

• 4+ years in AI/ML or DS roles.
• Experience deploying production ML solutions.
• Strong Python and ML framework experience.

Responsibilities

• Design, develop, train, evaluate, and deploy ML models.
• Build scalable ML pipelines for data processing and inference.
• Develop ML solutions using Python and frameworks.
• Work with supervised and unsupervised learning algorithms.
• Develop deep learning models with TensorFlow or PyTorch.
• Work with NLP, GenAI, LLMs, and RAG architectures.
• Deploy models into production using cloud and containers.
• Develop and maintain MLOps pipelines for CI/CD and monitoring.

Skills

Python

ML concepts

NLP & Generative AI

LLMs & embeddings

REST APIs

Git & GitHub

SQL

Docker

CI/CD

MLOps

TensorFlow

PyTorch

Scikit-learn

Pandas

NumPy

Education

Bachelor's or Master’s in CS/AI/DS

Tools

TensorFlow

PyTorch

Keras

Jupyter

Docker

Job description

Job Summary

We are seeking an experienced

Job Type: Full-Time

Work Model: Hybrid

Experience: 4+ Years

Employment: Full-Time

We are seeking an experienced AI/ML Engineer to design, develop, deploy, and maintain machine learning and artificial intelligence solutions. The ideal candidate will have strong experience in Python, Machine Learning, Deep Learning, NLP, Generative AI, LLMs, and MLOps, along with hands-on experience building and deploying scalable AI/ML applications in cloud environments.

The candidate will work closely with data scientists, software engineers, product teams, and business stakeholders to develop production-ready AI solutions.

Key Responsibilities

• Design, develop, train, evaluate, and deploy machine learning models.
• Build scalable AI/ML pipelines for data processing, model training, and inference.
• Develop machine learning solutions using Python and relevant ML frameworks.
• Work with supervised and unsupervised learning algorithms.
• Develop and optimize deep learning models using frameworks such as TensorFlow or PyTorch.
• Develop solutions involving NLP, Generative AI, LLMs, and Large Language Models.
• Work with LLM APIs, prompt engineering, embeddings, vector databases, and RAG (Retrieval-Augmented Generation) architectures.
• Fine-tune and optimize machine learning and AI models when required.
• Deploy AI/ML models into production environments using cloud and containerization technologies.
• Develop and maintain MLOps pipelines for continuous training, deployment, monitoring, and model lifecycle management.
• Perform model evaluation, validation, performance optimization, and troubleshooting.
• Collaborate with data engineers to prepare and transform large datasets for machine learning applications.
• Implement APIs and microservices to integrate AI/ML models with enterprise applications.
• Monitor model performance, accuracy, latency, and reliability in production.
• Ensure AI solutions are scalable, secure, maintainable, and cost-effective.
• Stay current with emerging AI/ML technologies, frameworks, and best practices.

Required Skills

• Strong programming experience with Python.
• Strong understanding of Machine Learning and Deep Learning concepts.
• Experience with Scikit-learn, TensorFlow, PyTorch, or similar frameworks.
• Experience with Pandas, NumPy, Matplotlib, and other data science libraries.
• Strong understanding of algorithms, statistics, probability, and model evaluation.
• Experience with NLP and Generative AI.
• Hands-on experience with LLMs, Prompt Engineering, RAG, embeddings, and vector databases.
• Experience with REST APIs and microservices.
• Experience with Git/GitHub and software development best practices.
• Knowledge of SQL and working with structured and unstructured data.
• Experience with Docker and containerized applications.
• Understanding of CI/CD and MLOps practices.

Cloud & MLOps

Experience With One Or More Of The Following

• AWS - SageMaker, Bedrock, EC2, S3, Lambda
• Azure - Azure Machine Learning, Azure OpenAI, Azure AI Services
• GCP - Vertex AI, BigQuery, Cloud Storage
• Kubernetes
• Docker
• MLflow
• Airflow
• Jenkins / GitHub Actions / Azure DevOps

Preferred Skills

• Experience with Generative AI and LLM application development.
• Experience with OpenAI, Azure OpenAI, Anthropic, or similar LLM platforms.
• Experience with vector databases such as Pinecone, FAISS, Weaviate, or Chroma.
• Experience building RAG-based applications and AI agents.
• Knowledge of LangChain, LlamaIndex, or similar frameworks.
• Experience with model optimization and inference performance.
• Knowledge of responsible AI, model security, and AI governance.
• Experience working in Agile/Scrum environments.

Education

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• Equivalent professional experience may be considered.

Qualifications

• 4+ years of professional experience in AI/ML, Data Science, or related engineering roles.
• Strong problem-solving and analytical skills.
• Ability to translate business requirements into scalable AI/ML solutions.
• Strong communication and collaboration skills.
• Ability to work independently as well as within a cross-functional team.
• Experience developing production-grade AI/ML applications.

Work Environment

Position: Full-Time

Work Arrangement: Hybrid

Schedule: Standard business hours, with flexibility based on business requirements

Location: [City, State]

Keywords

AI Engineer, Machine Learning Engineer, ML Engineer, Artificial Intelligence, Machine Learning, Deep Learning, Python, TensorFlow, PyTorch, Scikit-learn, NLP, Generative AI, GenAI, LLM, Large Language Models, RAG, Prompt Engineering, Vector Database, LangChain, LlamaIndex, MLOps, MLflow, AWS, Azure, GCP, SageMaker, Azure OpenAI, Vertex AI, Docker, Kubernetes, CI/CD, Data Science.

Skills

data science,learning,machine learning,data,azure,cloud,nlp,ml,models