Ai Ml Engineer / Freelancing WFH Opportunity

Codefactory Software Solutions; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Codefactory Software Solutions is seeking an experienced AI/ML Engineer with 5+ years of hands-on experience to design, develop, deploy, and maintain machine learning and artificial intelligence solutions. The role demands strong expertise in Python, ML, Deep Learning, NLP, Generative AI, LLMs, and MLOps, with a track record of moving models from experimentation to production.

You will design, train, and deploy ML models, work with NLP/LLM stacks, and build scalable APIs deployed on AWS, Azure,

Qualifications

• 5+ years of hands-on AI/ML engineering experience.
• Strong Python, ML/DL, NLP, Generative AI, LLMs, and MLOps expertise.
• Experience deploying ML solutions to production.
• Familiar with OpenAI, Azure OpenAI, Hugging Face, LangChain frameworks.
• Strong software engineering fundamentals and data-driven mindset.

Responsibilities

• Design, develop, train, and deploy ML/DL models for business applications.
• Analyze large datasets and perform data preprocessing, feature engineering, model selection, and optimization.
• Develop predictive models using supervised and unsupervised learning techniques.
• Work with NLP, Generative AI, LLMs, RAG, embeddings, and vector databases.
• Develop and integrate AI/ML solutions using OpenAI, Azure OpenAI, Hugging Face, LangChain, or similar frameworks.
• Build and optimize deep learning models using TensorFlow, PyTorch, or Keras.
• Develop scalable AI/ML APIs and integrate models into enterprise applications.
• Implement MLOps pipelines for model training, deployment, monitoring, and retraining.
• Deploy models using cloud platforms such as AWS, Azure, or GCP.
• Collaborate with Data Scientists, Data Engineers, Software Engineers, Product Managers, and business stakeholders.
• Monitor model performance, identify model drift, and improve accuracy and scalability.
• Conduct experimentation, A/B testing, model validation, and performance benchmarking.
• Ensure AI solutions meet requirements related to security, scalability, reliability, explainability, and responsible AI.
• Create technical documentation covering model architecture, experiments, APIs, deployment processes, and monitoring.

Skills

Python

SQL

REST APIs

OOP

Git/GitHub

Education

Bachelor's or Master’s in Computer Science/AI/Data Science/Engineering

Tools

OpenAI

Azure OpenAI

Hugging Face

LangChain

Job description

Job Summary

We are looking for an experienced AI/ML Engineer with 5+ years of hands‑on experience in designing, developing, deploying, and maintaining machine learning and artificial intelligence solutions. The ideal candidate should have strong expertise in Python, Machine Learning, Deep Learning, NLP, Generative AI, LLMs, and MLOps, with experience taking ML models from experimentation to production.

Key Responsibilities

• Design, develop, train, and deploy machine learning and deep learning models for business applications.


• Analyze large datasets and perform data preprocessing, feature engineering, model selection, and optimization.


• Develop predictive models using supervised and unsupervised learning techniques.


• Work with NLP, Generative AI, LLMs, RAG, embeddings, and vector databases.


• Develop and integrate AI/ML solutions using OpenAI, Azure OpenAI, Hugging Face, LangChain, or similar frameworks.


• Build and optimize deep learning models using TensorFlow, PyTorch, or Keras.


• Develop scalable AI/ML APIs and integrate models into enterprise applications.


• Implement MLOps pipelines for model training, deployment, monitoring, and retraining.


• Deploy models using cloud platforms such as AWS, Azure, or GCP.


• Collaborate with Data Scientists, Data Engineers, Software Engineers, Product Managers, and business stakeholders.


• Monitor model performance, identify model drift, and improve accuracy and scalability.


• Conduct experimentation, A/B testing, model validation, and performance benchmarking.


• Ensure AI solutions meet requirements related to security, scalability, reliability, explainability, and responsible AI.


• Create technical documentation covering model architecture, experiments, APIs, deployment processes, and monitoring.

Required Skills:-

Programming

• Python Advanced


• SQL


• REST APIs


• Object-Oriented Programming


• Git/GitHub

Machine Learning

• Regression


• Classification


• Clustering


• Decision Trees


• Random Forest


• XGBoost/LightGBM


• Feature Engineering


• Model Evaluation & Hyperparameter Tuning

Deep Learning

• Neural Networks


• CNN


• RNN/LSTM


• Transformers


• PyTorch / TensorFlow / Keras

Generative AI / LLM

• Large Language Models


• Prompt Engineering


• RAG


• Vector Embeddings


• Vector Databases


• LangChain / LlamaIndex


• OpenAI / Azure OpenAI


• Hugging Face


• Fine-tuning / PEFT / LoRA


• AI Agents and tool calling

Cloud & MLOps

• AWS / Azure / GCP


• Docker


• Kubernetes


• MLflow


• CI/CD


• Model Deployment


• Model Monitoring


• Data/ML Pipelines

Databases

• PostgreSQL / MySQL


• MongoDB


• Vector databases such as FAISS, Pinecone, Weaviate, or Chroma

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, or a related field.


• 5+ years of professional experience in AI/ML, Machine Learning Engineering, Data Science, or a related field.


• Experience deploying ML/AI solutions in production environments.


• Strong understanding of software engineering principles and system design.


• Experience working in Agile/Scrum environments.


• Strong analytical, problem-solving, communication, and stakeholder-management skills.