AI/ML Engineer

Winaxis LLC; Dallas (TX); On-site; USD 110,000 - 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 emphasizes ML/DL modeling, data pipelines, NLP, CV, and Generative AI with strong focus on deployment and governance.

You will build scalable pipelines, train models, and collaborate with data engineers, software developers, and business stakeholders to deliver AI capabilities at scale.

Qualifications

• Degree in CS/AI/DS/Math/Statistics or related field.
• Strong Python development skills.
• Experience with ML libraries: TF, PyTorch, Scikit-learn, XGBoost.
• Knowledge of ML/DL, NLP, CV, RL concepts.
• Experience with SQL and NoSQL databases.
• Familiarity with Docker, Kubernetes, MLflow, cloud platforms.
• Version control with Git.

Responsibilities

• Design, develop, train, and optimize ML/DL models.
• Build scalable data pipelines for training and inference.
• Develop AI apps using NLP, CV, Generative AI, and predictive analytics.
• Deploy models in production with MLOps practices.
• Work with large datasets, preprocessing, feature engineering, evaluation.
• Collaborate with data engineers, software teams, and stakeholders.
• Monitor models and implement continuous improvements.
• Research emerging AI tech, frameworks, and trends.
• Develop APIs and microservices for AI integration.
• Ensure data security, governance, and compliance.

Skills

Python programming

Machine Learning

Deep Learning

NLP

Computer Vision

Reinforcement Learning

Data processing

SQL

NoSQL databases

Git

Cloud platforms

Education

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

Tools

TensorFlow

PyTorch

Scikit-learn

XGBoost

Docker

Kubernetes

MLflow

Apache Spark

LangChain / LlamaIndex / Hugging Face

OpenAI APIs

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)