AI Engineer

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Hiring W2 Candidates Only

Visa: Open To Any Visa Type With Valid Work Authorization In the USA

Job Summary

We are seeking a talented AI Engineer to design, develop, and deploy artificial intelligence and machine learning solutions that solve complex business problems. The ideal candidate will have a solid foundation in data science, software engineering, and cloud-based AI tools, with the ability to operationalize AI models at scale.

Key Responsibilities

• Design, develop, and implement machine learning (ML) and deep learning (DL) models to address business and operational challenges.
• Collaborate with data scientists, data engineers, and software developers to build end-to-end AI pipelines.
• Preprocess, clean, and analyze large datasets to ensure data quality and usability.
• Deploy and monitor ML models in production environments (on-premise or cloud).
• Optimize model performance through hyperparameter tuning, feature engineering, and model retraining.
• Build and integrate AI APIs, including NLP, computer vision, and predictive analytics components.
• Develop automation scripts and reusable frameworks for model training and inference.
• Work with cloud AI services (AWS SageMaker, Azure AI, Google Vertex AI) to scale solutions.
• Document workflows, model architectures, and deployment procedures.
• Stay current on emerging AI trends, frameworks, and best practices.
  
  

Required Skills And Qualifications

• Bachelor s or Master s degree in Computer Science, Data Science, Artificial Intelligence, or related field.
• 3 years of experience in AI/ML engineering or applied machine learning.
• Strong proficiency in Python and libraries such as TensorFlow, PyTorch, scikit-learn, NumPy, pandas.
• Experience with ML lifecycle management from data preprocessing to deployment and monitoring.
• Solid understanding of machine learning algorithms, neural networks, and statistical modeling.
• Hands-on experience with cloud AI platforms (AWS SageMaker, Azure ML, Google Vertex AI).
• Experience building and consuming RESTful APIs and working with microservices architectures.
• Familiarity with data pipelines, ETL processes, and data versioning tools (e.g., DVC, MLflow).
• Strong understanding of MLOps, CI/CD, and containerization (Docker, Kubernetes).
• Excellent communication skills and ability to work collaboratively across multidisciplinary teams.
  
  

Preferred / Nice-to-Have Skills

• Experience with Natural Language Processing (NLP) using Hugging Face, spaCy, or transformers.
• Exposure to computer vision (OpenCV, YOLO, Detectron2).
• Knowledge of reinforcement learning or generative AI (LLMs, diffusion models).
• Experience with big data tools (Spark, Hadoop) and data lakes.
• Familiarity with DevOps and model observability tools (Prometheus, Grafana, EvidentlyAI).
• Contributions to open-source AI projects or publications in AI/ML.
  
  

Example Technology Stack

Languages: Python, SQL, Bash

Libraries/Frameworks: TensorFlow, PyTorch, scikit-learn, Keras, Transformers

Tools: MLflow, Airflow, Docker, Kubernetes, Git

Cloud: AWS SageMaker, Azure ML, Google Vertex AI

Databases: PostgreSQL, MongoDB, BigQuery, Snowflake

Soft Skills

• Strong analytical and problem-solving ability.
• Curiosity for emerging AI trends and practical applications.
• Excellent teamwork and communication in cross-functional environments.
• Ability to explain technical AI concepts to non-technical stakeholders.