AI/ML Engineer

Winaxis LLC; Dallas (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Winaxis LLC in Dallas seeks an AI/ML Engineer to design, develop, and deploy machine learning solutions that tackle real-world business problems. You will build scalable data pipelines, train models, and deploy them in cloud environments leveraging MLOps practices.

The role requires strong Python skills and hands-on experience with ML libraries like TensorFlow, PyTorch, Scikit-learn, and XGBoost, plus familiarity with SQL/NoSQL, Docker, Kubernetes, MLflow, and cloud platforms (AWS/Azure/GCP).

Qualifications

• Bachelor's or Master's degree in Computer Science, AI, Data Science, Mathematics, Statistics, or a related field.
• Strong programming skills in Python.
• Experience with ML libraries such as TensorFlow, PyTorch, Scikit-learn, XGBoost.
• Strong understanding of supervised/unsupervised learning, deep learning, neural networks, NLP, computer vision, reinforcement learning (preferred).
• Experience with SQL and NoSQL databases.
• Knowledge of model deployment frameworks such as Docker, Kubernetes, and MLflow.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with version control systems like Git.
• Experience with Generative AI technologies and LLMs (Nice to Have).
• Hands-on experience with LangChain, LlamaIndex, Hugging Face, OpenAI APIs, and vector databases (Pinecone, Weaviate, ChromaDB, FAISS) (Nice to Have).
• Experience in Retrieval-Augmented Generation (RAG) and MLOps CI/CD pipelines (Nice to Have).
• Knowledge of Databricks and Apache Spark (Nice to Have).

Responsibilities

• Design, develop, train, and optimize Machine Learning and Deep Learning models.
• Build and maintain scalable data pipelines for model training and inference.
• Develop AI-powered applications using NLP, Computer Vision, Generative AI, and predictive analytics techniques.
• Deploy machine learning models into production environments using MLOps best practices.
• Work with large datasets and perform data preprocessing, feature engineering, and model evaluation.
• Collaborate with data engineers, software developers, and business stakeholders to understand requirements and deliver AI solutions.
• Monitor model performance and implement continuous improvements.
• Research and evaluate emerging AI technologies, frameworks, and industry trends.
• Develop APIs and microservices for AI model integration.
• Ensure data security, model governance, and compliance standards are maintained.

Skills

Python

ML libraries (TensorFlow)

ML libraries (PyTorch)

ML libraries (Scikit-learn)

ML libraries (XGBoost)

Deep Learning

NLP

Computer Vision

Reinforcement Learning

SQL

NoSQL

Docker

Kubernetes

MLflow

AWS

Azure

GCP

Git

Generative AI

LLMs

Education

Bachelor's or Master's in Computer Science / AI / Data Science / Mathematics / Statistics

Tools

Docker

Kubernetes

MLflow

Databricks

Apache Spark

LangChain

LlamaIndex

Hugging Face

OpenAI APIs

Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS)

Git

Job description

About the Role: We are seeking a talented and innovative AI/ML Engineer to design, develop, and deploy machine learning and artificial intelligence solutions that solve real-world business problems. The ideal candidate should have strong expertise in machine learning algorithms, data processing, model deployment, and cloud technologies.

Key Responsibilities

• Design, develop, train, and optimize Machine Learning and Deep Learning models.
• Build and maintain scalable data pipelines for model training and inference.
• Develop AI-powered applications using NLP, Computer Vision, Generative AI, and predictive analytics techniques.
• Deploy machine learning models into production environments using MLOps best practices.
• Work with large datasets and perform data preprocessing, feature engineering, and model evaluation.
• Collaborate with data engineers, software developers, and business stakeholders to understand requirements and deliver AI solutions.
• Monitor model performance and implement continuous improvements.
• Research and evaluate emerging AI technologies, frameworks, and industry trends.
• Develop APIs and microservices for AI model integration.
• Ensure data security, model governance, and compliance standards are maintained.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, Statistics, or a related field.
• Strong programming skills in Python.
• Experience with Machine Learning libraries such as: TensorFlow PyTorch Scikit-learn XGBoost.
• Strong understanding of: Supervised and Unsupervised Learning Deep Learning Neural Networks Natural Language Processing (NLP) Computer Vision Reinforcement Learning (preferred).
• Experience with SQL and NoSQL databases.
• Knowledge of model deployment frameworks such as Docker, Kubernetes, and MLflow.
• Experience working with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with version control systems like Git.

Preferred Qualifications

• Experience with Generative AI technologies and Large Language Models (LLMs).
• Hands-on experience with: LangChain LlamaIndex Hugging Face OpenAI APIs Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS).
• Experience in RAG (Retrieval-Augmented Generation) implementations.
• Knowledge of MLOps tools and CI/CD pipelines.
• Experience with Databricks and Apache Spark.

Technical Skills

• Python
• SQL
• TensorFlow
• PyTorch
• Scikit-learn
• Pandas
• NumPy
• Apache Spark
• MLflow
• Docker
• Kubernetes
• AWS/Azure/GCP
• Git
• REST APIs
• Generative AI & LLMs

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and collaboration skills.
• Ability to work independently and in a team environment.
• Strong attention to detail and commitment to quality.

Nice to Have

• AI Agent Development
• Multi-Agent Systems
• Prompt Engineering
• Fine-tuning LLMs
• Knowledge Graphs
• MLOps Certification
• Cloud Certifications (AWS, Azure, GCP)