AI Engineer

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

• Bachelors or Masters 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.