AI/ML Engineer

Winaxis LLC; Dallas (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

Winaxis LLC is seeking an AI/ML Engineer to design, develop, and deploy ML/AI solutions that solve real-world business problems. The role requires strong expertise in ML algorithms, data processing, model deployment, and cloud technologies.

The candidate will design, train, and optimize ML/DL models, build data pipelines, and deploy AI-powered applications using NLP, CV, and generative AI techniques with MLOps practices. Collaboration with data engineers and software teams is essential.

Qualifications

• Bachelor's or Master's in CS/AI/Data Science or related field.
• Proficient in Python programming.
• Experience with ML libraries like TensorFlow, PyTorch, Scikit-learn.

Responsibilities

• Design, develop, train, and optimize ML/DL models.
• Build scalable data pipelines for training and inference.
• Develop AI applications using NLP, CV, Generative AI, predictive analytics.

Skills

Python

TensorFlow

PyTorch

Scikit-learn

XGBoost

NLP

Computer Vision

Reinforcement learning

ML deployment

MLOps

Docker

Kubernetes

AWS/Azure/GCP

REST APIs

Git

Databricks / Spark

Education

Bachelor's or Master's in CS/AI/Data Science etc.

Tools

Docker

Kubernetes

MLflow

Apache Spark

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)