AI/ML Engineer
Raas Infotek LLC
Plano, United States of America
yesterday
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
SeniorJob location
Plano, United States of America
Tech stack
Java
A/B testing
API
Artificial Intelligence
Airflow
Amazon Web Services (AWS)
Computer Vision
Azure
Big Data
Cloud Computing
Continuous Integration
Information Engineering
Data Transformation
Data Security
DevOps
Distributed Systems
Hadoop
Monitoring of Systems
Python
Machine Learning
Natural Language Processing
NoSQL
Performance Tuning
Scrum
Recommender Systems
TensorFlow
Standard Sql
Software Engineering
Unstructured Data
Google Cloud Platform
Enterprise Software Applications
Feature Engineering
Data Ingestion
PyTorch
Large Language Models
Prompt Engineering
Spark
Deep Learning
Model Validation
Generative AI
Keras
Containerization
Scikit Learn
Kubernetes
Information Technology
Low Latency
XGBoost
Kafka
Machine Learning Operations
REST
Software Version Control
Docker
Jenkins
Microservices
Job description
We are seeking an experienced AI/ML Engineer with 10+ years of industry experience in designing, developing, and deploying scalable Artificial Intelligence and Machine Learning solutions. The ideal candidate will have strong expertise in machine learning algorithms, deep learning frameworks, data engineering, MLOps, cloud platforms, and production-grade AI systems. This role requires collaboration with cross-functional teams to deliver innovative AI-driven solutions that support business objectives., * Design, develop, and deploy scalable Machine Learning and AI models for enterprise applications.
- Build and optimize predictive models, recommendation systems, NLP solutions, and deep learning architectures.
- Develop end-to-end ML pipelines including data ingestion, preprocessing, feature engineering, model training, evaluation, deployment, and monitoring.
- Work with large-scale structured and unstructured datasets using distributed computing technologies.
- Implement MLOps practices for CI/CD, model versioning, monitoring, retraining, and governance.
- Collaborate with data engineers, software developers, product managers, and business stakeholders to define AI/ML solutions.
- Optimize model performance, scalability, reliability, and latency in production environments.
- Utilize cloud platforms such as AWS, Azure, or Google Cloud Platform for AI/ML workloads and deployments.
- Develop APIs and microservices for ML model integration into enterprise systems.
- Conduct experimentation, model tuning, A/B testing, and performance evaluation.
- Ensure compliance with data security, privacy, and responsible AI standards.
- Mentor junior engineers and contribute to AI/ML best practices and technical leadership initiatives.
- Stay updated with emerging AI/ML technologies, frameworks, and industry trends.
Requirements
- 10+ years of experience in Software Engineering, Data Science, AI/ML Engineering, or related fields.
- Strong expertise in Machine Learning, Deep Learning, NLP, Computer Vision, or Generative AI technologies.
- Proficiency in Python, Java, or Scala.
- Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, or XGBoost.
- Experience with Generative AI, LLMs, Prompt Engineering, RAG architectures, LangChain, or vector databases.
- Strong knowledge of MLOps tools such as MLflow, Kubeflow, Airflow, Docker, Kubernetes, or Jenkins.
- Experience with cloud platforms: AWS, Microsoft Azure, or Google Cloud Platform.
- Strong SQL and NoSQL database experience.
- Experience with big data technologies such as Spark, Hadoop, or Kafka.
- Knowledge of REST APIs, microservices architecture, and containerization technologies.
- Familiarity with model deployment and monitoring tools.
- Excellent analytical, problem-solving, and communication skills.
- Ability to work in Agile/Scrum development environments., * Experience with Generative AI platforms and LLM integration.
- Knowledge of AI ethics, governance, and responsible AI practices.
- Experience in enterprise-scale AI implementations.
- Exposure to DevOps and CI/CD automation processes.
- Relevant certifications in AI/ML or Cloud technologies are a plus., * Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, or related field.
- Master's degree in Artificial Intelligence, Machine Learning, Computer Science, or a related discipline preferred.