AI Engineer

Goldenpick Technologies

Houston, TX, United States

19 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Java (Programming Language) Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Computer Vision Cloud Computing Databases Information Engineering Extract Transform Load (ETL) Data Transformation DevOps Distributed Systems

+30 more

Github Python (Programming Language) Machine Learning NoSQL NumPy Tensorflow Azure Machine Learning SQL Databases Data Streaming Systems Integration Unstructured Data Feature Engineering Pytorch Large Language Models Prompt Engineering Apache Spark Backend Git Pandas Gitlab-ci Scikit Learn Low Latency HuggingFace Machine Learning Operations Front End Software Development Software Version Control Data Pipelines Docker Jenkins Microservices

Job description

AI/ML Model Development
Design, develop, and optimize machine learning and deep learning models
Build NLP, computer vision, or predictive analytics solutions
Train, test, and evaluate models for accuracy, scalability, and performance
Fine-tune pre-trained models (e.g., LLMs, transformers) for business use cases
Data Engineering & Processing (Optional)
Collect, clean, and preprocess structured and unstructured datasets
Work with large-scale data pipelines and streaming data systems
Implement feature engineering and data transformation workflows
Deployment & MLOps
Deploy models into production using APIs, containers, or microservices
Work with DevOps to build CI/CD pipelines for ML workflows (MLOps)
Monitor model performance, drift, and reliability in production
Optimize latency, throughput, and cost efficiency
Cloud & System Integration
Integrate AI solutions into cloud platforms (AWS)
Work with services like SageMaker, Azure ML, Vertex AI, or OpenAI APIs
Collaborate with DevOps, backend, and frontend teams for implementation
Research & Innovation
Stay up to date with emerging AI technologies and frameworks
Evaluate and implement GenAI, LLMs, and prompt engineering techniques
Prototype and experiment with new AI-driven solutions

Requirements

Skills Must have

Programming: Python (preferred), Java, or Scala
ML Frameworks: TensorFlow, PyTorch, Scikit-learn
AI/GenAI: prompt engineering (preferred), Claude CLI / Code(preferred), LLMs(preferred) Hugging Face, OpenAI APIs
Data Tools (Optional): Pandas, NumPy, Spark
APIs & Microservices development
Version control (Git)
Cloud & DevOps
Experience with AWS
Containers: Docker, ECS/EKS
CI/CD pipelines (GitHub Actions Or Jenkins Or GitLab CI)
Data & Systems
Databases: SQL, NoSQL
Familiarity with data pipelines and ETL processes (Optional)
Understanding of distributed systems